The Power of Artificial Intelligence - US Congressional Hearing, June 26th, 2018

all right without objection the chair is authorized to declare recesses of the committee at any time good morning and welcome to today's hearing entitled

artificial intelligence with great power comes great responsibility I now recognize myself for five minutes for an

opening statement first I would like to note that one of our witnesses dr. jaime

carbonell from Carnegie Mellon Mellon University is unable to be here today due to a medical emergency we wish him well and a speedy recovery and without objection

we'll ensure his written testimony is made part of the hearing record one of the reasons I've been looking forward to today's hearing is to get a better sense from our witnesses about the nuances of

the term artificial intelligence and implications for our society in a future where AI is ubiquitous of course one

might say AI is already pervasive since the term was first coined in the 1950s we have made huge advances in the field of artificial narrow intelligence which has been applied to many familiar

everyday items such as the technology underlying Siri and Alexa called Ani for short such systems are designed to conduct specific and usually limited

tasks for example a machine that excels at playing poker wouldn't be able to parallel park a car conversely AG AI or artificial general intelligence refers

to intelligent behavior across a range of cognitive tasks if you enjoy science fiction movies this definition may conjure up scenes from any number of classics such as Blade Runner the matrix

or The Terminator for many individuals the term AGI invokes images of robots or machines with human to intelligence as it turns out we are decades away from realizing

such AGI systems nevertheless discussions about AGI in a future in which AGI is commonplace lead to some interesting questions

worthy of analysis for example Elon Musk has said has been quoted as saying that AI quote is a fundamental risk to the

existence of human civilization and poses vastly more risk than North Korea does that mean that AGI may evolve to a point one day when we will lose control

over machines of our own creation as far-fetched as that sounds minds and scientists are certainly discussing such questions for the short term however my constituents are

concerned about less existential issues that usually accompany new and evolving technologies topics such as cybersecurity protecting our privacy and

impacts to our nation's economy and to jobs I'm an original co-sponsor of a bill introduced earlier this year titled the AI Jobs Act of 2018

to help our workplace prepare for the ways AI will shape the economy of the future I will also introduce legislation today to reauthorize the National Institute of Standards and Technology

which includes language directing NIST to support development of artificial intelligence in data science there is immense potential for AGI to help humans

and to help our economy and all of the issues were dealing with today but that potential is also accompanied by some of the concerns that we will discuss today I look forward to what our panel has to

share with us about the bright as well as the challenging sides of the future with AGI I now recognize the ranking member of the research and Technology

subcommittee the gentleman from Illinois mr. Lipinski for his opening statement thank you cheering Comstock and Thank You Jaron Webber for holding this

hearing to understand the current state of artificial intelligence technology because of the rapid development of computational power its capacity of AI

to perform new and more complicated tasks is quickly advancing depending on who you ask AI is the stuff of dreams or nightmares

I believe is definitely the former and I strongly fear that could also be the latter the science fiction/fantasy world's depicted on Hollywood big and

small screens alike capture imaginations about what the world might be like if humans and highly intelligent robots shared the earth today's hearing is an

opportunity to begin to understand the real issues in AI and to begin to move forward with informed science-based

policymaking this is a hearing that we may remember years from now hopefully as a bright beginning of a new era current

AI technologies touch a broad scope of industries and sectors including manufacturing transportation energy healthcare and many others as we will

hear from the witnesses today artificial intelligence can be classified as artificial general intelligence or artificial narrow intelligence from my

understanding is applications of the latter such as machine learning there are underlying technologies that support some of the services and devices widely used by Americans today these include

virtual assistance such as Siri and Alexa translation services such as google translate in autonomous vehicle technologies as the capability is

available and I'd like undoubtedly become a more essential part of our lives in our economy while technology developers an industry look forward to

making great strides in AI I want to make sure my colleagues and I in Congress are asking the tough questions and carefully considering the most crucial roles that the federal

government may have in shaping the future of AI federal investments in AI research are long-standing we must consider the appropriate balance and

scope of federal involvement as we begin to better understand the various roles AI will play in our society we are not starting from scratch in thinking about

the appropriate role of the federal government in this arena in 2016 the White House issued the National artificial intelligence research and development strategic plan

that outlines seven priorities for federally-funded AI research these included making long-term investments in AI developing effective methods for

human AI collaboration and addressing the ethical legal and societal implications of AI additional issues to

address our safety in security public data sets standards in workforce needs earlier this year the Government Accountability Office issued a

technology assessment report led by one of our witnesses dr. Pearson's titled artificial intelligence emerging opportunities challenges and implications while noting significant

potential for AI to improve many industries including finance transportation and cyber security the report also noted areas where research is still needed including how to

optimally regulate AI how to ensure the availability and use of high-quality data understanding ai's effects unemployment in education and the

development of computational ethics to guide the decisions made by software these are all critical issues but more and more I hear concern in widely

varying predictions about a i's impact on jobs AI has potential to make some job function safer and more efficient but also may replace others we need to

ask what are the long-term projections for the job market is AI grows in this context we also need to ask how well do our AI capabilities compared to those of

other countries what education skills and Retraining will a workforce of the future need these are very important questions as we think about ensuring a skilled workforce for the future that

will help solidify US leadership in AI as other countries vie for dominance in the field if AI threatens some careers it likely creates many others we need to

consider what Congress should do to shape this impact and make sure Americans are ready for it and make sure the benefits of a a AI are distributed widely

another obvious issue of major concern when it comes to AI is ethics there are many places where this becomes relevant currently we need to grapple with issues

regarding the data that are being used to educate machines by state will lead to bias results from seemingly objective machines a little further down the line

are many difficult questions being raised in science fiction about a world of humans and intelligent robots these are questions we likely be called on to

deal with in Congress and we need to be ready I want to thank all of our witnesses for being here today and I look forward to your testimony now yield

back thank you mr. Lipinski and I now recognize the chairman of the energy subcommittee the gentleman from Texas mr. Weber for his opening statement

madam chair can I defer to the chairman of the full committee for his statement yes he may thank you thank you madam chair Thank You mr. chairman didn't know

you're going to do that matter share often unknown to us advances in artificial intelligence or AI touch many aspects of our lives in the area of

cybersecurity AI reduces our reaction times to security threats in the field of agriculture AI monitors soil moisture and targets crop watering and in the

transportation lane AI steers self-driving cars and manages intelligent traffic systems multiple technical disciplines including quantum

computing science converge to form AI tomorrow the science committee will mark up the National quantum initiative Act which establishes a federal program to accelerate quantum research and

development this is a bipartisan bill that ranking member Eddie Bernice Johnson and I and others will introduce today my hope is that every member of the committee will sponsor it or at

least a majority transforming our current quantum research into real-world applications will create scientific and technological discoveries especially in the field of artificial intelligence

these discoveries will stimulate economic growth and improve our global competitiveness important considerations in light of China's advances in artificial

intelligence and quantum computing by some accounts China is investing 7 billion dollars in AI through 2030 and

10 billion in quantum research the European Union has also issued a preliminary plan outlining a 24 billion dollar public private investment in AI

between 2018 and 2020 and Russian President Putin has noted that quote the leader in AI will rule the world in

quote no doubt that's appealing to him yet the Department of Defense's unclassified investment in AI was only six hundred million in 2016 while

federal spending on quantum totals only about two hundred and fifty million dollars a year the committee will mark up a second piece of legislation to reauthorize the National Institute of

Standards and Technology the bill directs NIST to continue supporting the development of artificial intelligence and data science including the development of machine learning and other artificial intelligence

applications it is simply vital to our nation's future that we accelerate our quantum computing and artificial intelligence efforts and thank you madam

chair and yield back thank you and I now recognize let's see where we are the ranking member of the energy subcommittee the gentleman from Texas

mr. VC for an opening statement I want to thank you chair woman Comstock and chairman Weber for holding this hearing today and thank you for all of the witnesses for providing expertise on

this topic I'm looking forward to hearing what everyone has to say today America of course is a country of innovation and in the digital world of today more and more industries are relying on advanced technologies and

connectivity to overcome new challenges artificial intelligence and big data are impacting every facet of production and commerce AI has the ability to mimic

cognitive functions such as problem-solving and learning making it a critical resources we encounter never-before-seen problems those in the energy sector have already seen improvements and

productivity and efficiency and can expect to see even more advancement in the coming years AI can be used to process and analyze

data and previously unexplored ways technologies such as sensor equipped aircraft engines locomotive gas and wind turbines are now able to track

production efficiency and wear and tear on vital machinery AI could also significantly improve our ability to detect failures before they occur and

prevent disasters saving money time and lives and through the use of analytics since there's an operational data hey I can be used to manage maintain and

optimize systems ranging from energy storage components to power plants to the electric grid as digital technologies revolutionize the energy sector we must ensure safe and

responsible execution of these processes AR systems can learn adapt through continuous modeling of interaction and data feedback production must be put in

place to guarantee the integrity of these mechanisms as they evaluate mass quantities of machine and user data with Americans right to privacy under threat

security of these connected systems is of the utmost importance nevertheless I'm excited to learn about the valuable benefits today I may be able to provide for our economy and our

well-being alike with a Gartner research study reporting that AI will generate 2.3 million jobs by 2020 that's a lot of jobs the growth AI will bring not only

to the energy sector but to healthcare transportation education and so many others will help ensure the prosperity of our nation I look forward to seeing

what light our witnesses can shed on these topics and what we can do in Congress to help enable the development and deployment of these promising technologies madam chairwoman I yield back the balance of my time

thank you and I now recognize mr. Weber for his opening statement thank you madam chair today we will hear from a panel of experts on next-generation artificial intelligence AI as we've all

heard it described and while some have raised concerns about the negative consequences of AI this technology has the potential to solve fundamental science and improve

fundamental science problems and improve everyday life in fact it's likely that everyone in this room benefits some artificial intelligence for example

users of voice assistance online purchase prediction fraud detection that the gentleman takes us mentioned and music recommendation services are

already utilizing aspects of this technology in their day-to-day life in the past few years the use of AI technology has rapidly expanded due to

the increase in the volume of data worldwide and to the proliferation of advanced computing hardware that allows for the powerful parallel processing of

this data the field of AI has broadened to include other advanced computing disciplines such as machine learning we've heard about neural networks deep learning computer vision and natural

language processing just to name a few these learning techniques are key to the development of AI technologies and can be used to explore complex relationships

and produce previously unseen results on unprecedented timescales the Department of Energy the OE is the nation's largest

federal supporter of basic research in the physical science sciences with expertise in big data science high-performance computing advanced

algorithms and data analytics and is uniquely positioned to enable fundamental research in AI and machine learning do ease office of science

advanced scientific computing research program or Oscar as we call it a program develops next-generation supercomputing systems that can achieve the

computational power needed for this type of critical research this includes the department's newest and most powerful supercomputer call summit which just

yesterday just yesterday was ranked as the fastest computing system in the end world AI also has brought applications

in the deal mission space in material science AI helps researchers speed the experimental process and discover new compounds faster than ever before

in high-energy physics AI finds patterns in atomic and particle collisions previously unseen by scientists in fusion energy research AI modelling

predicts plasma behavior that will assist in building tokamak reactors making the best of our investments in space even in fossil fuel energy

production ai systems will optimize efficiency and predict needed maintenance at power generating facilities ai technology has the

potential to improve computational science methods for any big data problem any big data problem and with the next generation of supercomputers the

exascale computing systems that do is do is expected to feel by 2021 American researchers utilizing AI technology will

be able to track even the bigger challenges we cannot afford to fall behind in this compelling area of research and big investments in AI by

China and Europe already threatened u.s.

dominance in this field with the immense potential for AI technology to answer fundamental scientific challenges it's quite clear we should prioritize this

research we should maintain I will add American competitive edge and American exceptionalism this will help us to do that I want to thank our accomplished

panel of witnesses for their testimony today and I look forward to hearing what role Congress can play and should play in advancing this critical area of discovery science and madam chair I yield back

thank you and I will now introduce today's witnesses our our first witness today is dr. Tim person's chief scientists at the US Government

Accountability Office he also serves as the director for Gao Center for science technology and engineering dr. Parsons received a Bachelor of Science and physic

from James Madison University and a Master of Science in nuclear physics from Emory University he also earned a Master of Science in computer science

and PhD and biomedical engineering both from Wake Forest University next we have mr. Greg Brockman our second witness who

is co-founder and chief technology officer of open AI a non-profit artificial intelligence research company mr. Brockman is an investor in over 30

startups and a board member of the stellar digital currency system he was previously the CTO of stripe a payments

startup now valued at over 9 billion and he studied mathematics at Harvard and computer science at MIT and our final witness is dr. Fei Fei

Li Li chairperson of the board and co-founder of AI for all in addition dr. Li is a professor in the computer science department at Stanford and the

director of the Stanford artificial intelligence lab in 2017 dr. Li also joined Google cloud as chief scientist of API and machine learning dr. Lee

received a Bachelor of Arts degree in physics from Princeton and her PhD in electrical engineering from the California Institute of Technology I now recognize dr. persons for five minutes

to present his testimony good morning thank you chairman Kahn stock chairman Weber ranking members Lipinski and VZ and members of the subcommittee I'm pleased to be here today to discuss Gao

s technology assessment on artificial intelligence to ensure the u.s. remains

a leader in AI innovation special attention will be needed for our education and training systems regulatory structures frameworks for privacy and civil liberties and our

understanding of risk management in general AI holds substantial promise for improving human life increasing the nation's economic competitiveness and

solving some of society's most pressing challenges yet as a disruptive technology I opposes risks that could have far-reaching effects on for example

the future labor force economic and and privacy and civil liberties among others today I'll summarize three key insights arising from our recent work

first the distinction between narrow versus general AI the second the expected impact of AI on jobs competitiveness and workforce training and third the role the federal

government can play in research standards development new regulatory approaches and education regarding narrow versus general AI narrow AI

refers to applications that are tasks specific such as tax preparation software voice and face recognition systems and algorithms that classify the

content of images general AI refers to a system exhibiting intelligence on par with or possibly exceeding that at humans while science fiction has helped

general AI capture our collective imaginations for some time it is unlikely to be fully achieved for decades if at all even so considerable

progress has been made in developing narrow AI applications that outperform humans and specific tasks and are thus invoking crucially important economic policy and research considerations

regarding jobs competition in the workforce there is considerable uncertainty about the extent to which jobs will be displaced by AI and how

many how much any losses will be offset by job creation in the near term displacement to certain jobs such as call center or retail workers may be

particularly vulnerable to automation however in the long term demand for skills that are complementary to AI is expected to increase resulting in greater productivity to better

understand the impact of AI on employment moving forward several experts underscored the need for new data and methods to enable greater insight into this issue regarding the

role of the federal government it will continue its crucial role in research and data sharing contributions to standards development regulatory approaches and education what important

research area the federal government could support is enhancing the explained ability of AI which could help establish trust in the behavior of AI systems the Durrell government could also

incentivize data sharing including federal data that are subject to limitations for how they can be used as well as creating frameworks for sharing data to improve the safety and security

of AI systems such a include supporting standards for explain ability data labeling and safety including risk assessment and benchmarking of AI

performance against the status quo it's always risk versus risk related to this new regulatory approaches are needed including the development of regulatory

sandboxes for testing AI products services and business models especially in industries like transportation financial services and healthcare

Gao s recent report on fen tech found for example that regulators use sandboxes to gain insight into key questions issues and unexpected risks that may arise out of the emerging

technologies new rules governing intellectual property and data privacy may also be needed to manage the deployment of a I finally education and training will need to be reimagined so

workers have the skills needed to work with and alongside emerging AI technologies for the u.s. to remain

competitive globally and effectively manage AI systems its workers will need a deeper understanding of probability and statistics across most if not all academic disciplines that is not just

the physical engineering and biological sciences as well as competency in ethics algorithmic audit ability and risk management in conclusion the emergence of what some have called the fourth

Industrial Revolution and a eyes key role in driving it will require new frameworks for business models and value propositions for the public and private sectors alike even if AI technologies

were to cease advancing today no part of society or the economy would be directly or indirectly untouched by its transformative effects I thank committee

leadership committees thanks to the members here for your holding a hearing on this very important topic today for such a time as this madam chairwoman mr.

chairman ranking members this concludes my prepared remarks I would be happy to respond to any questions that you or other members of the subcommittees have at this time thank you and I now recognize mr. Brockman for

five minutes chairwoman Comstock chairman Weber ranking member Lipinski ranking member VC members of both subcommittees thank you for having me today to deliver testimony

I'm Greg Brockman co-founder of open a high a San Francisco based nonprofit with the mission to ensure that artificial general intelligence which we defined as systems highly autonomous systems that outperform humans at most

economically valuable work benefits all of humanity now I'm here to tell you about the generality of modern AI y AG I might actually be in reach sooner than commonly expected and what action

policymakers can take today so first what's open AI we're a research company with one of the world's most advanced AI research and development teams yesterday we announced major progress towards a milestone that we alphabet subsidiary

deep mind and Facebook have separately been trying to reach which is solving complex strategy games which start to capture many aspects of the real world that were just not seen in board games like chess ergo we built a system called

open AI 5 which learned to devise long term plans and navigate scenarios far too complex to be programmed in by a human in order to solve a massively popular competitive game called dota 2

now in the past AI like technology was written by humans in order to solve one specific problem at a time it was not capable of adapting to solve new problems today's AI is all based on one core

technique which is the artificial neural network a single simple idea that as it's run on faster computers is proving to match a surprising amount of human capability and this was in fact something that was shown in part by my

fellow witnesses dr. Lee's work and image recognition and artificial neural networks can be trained to perform speech recognition or computer vision it just depends on the data that they're shown now further along the spectrum of

generality is AGI rather than being developed for any one use case a ji would be developed for a wide range of important tasks an AGI would also be useful for non commercial applications including thinking through complex

international disputes or City Planning now people have been talking about AGI for decades and so how should we think about the timeline well all AI systems they're built on three foundations

that's data computational power and algorithms next generation AI systems are already starting to rely less on conventional data sets human has provided the right answer for

example one of our recent neural networks learned by reading 7,000 books we also recently released a study showing that the amount of computation powering the largest AI training runs

has been doubling every three and a half months since 2012 that's a total increase of 300,000 times and we expect this to continue for the next five years using only today's proven hardware

technologies and not assuming any breakthroughs like quantum or optical now to put that into perspective that's like if your phone battery which today lasts for a day started to last for 800

years and then five years later started to last for 100 million years it's this torrent of compute this the tsunami of compute we've never seen anything like this and so the open question is will

this massive increase in computational power combined with near-term improvements in algorithmic understanding be enough to develop AGI we don't know the answer to this question today but given the rapid

progress that we are seeing we can't confidently ruled out and so now what should we be thinking about today what what can policymakers be doing today and so you know the first thing to recognize

is the core danger of AGI is that it has fundamentally the potential to cause rapid change whether that's through machines pursuing goals that are misspecified by their operator whether it's through malicious humans subverting

deployed systems or whether it's an economy that grows in an out-of-control way for its own sake rather than in order to improve human lives now we spent two years worth of policy

research to create the open high Charter which in fact is a document I have right here in front of me this contains three sections defining our views on safe and responsible AGI development so that's one is leaving

time for safety and in particular refusing of race to the bottom on safety in order to reach AGI first the second is to ensure the people at large rather than any one small group receive the benefits of this transformative

technology and the third is working together as a community in order to solve safety and policy challenges now our primary primary recommendation to policy makers is to start measuring

progress in this field we need to understand how fast the field is moving what capabilities are likely to arrive when in order to successfully plan for AGS challenges that move towards forecasts rather than intuition

measurements also place where international coordination actually valuable and this is important if we want to spread safety and ethical standards globally so thank you for your time and I look forward to questions

thank you and we're never he knows dr. Lee thank you for the invitation congresswoman and Congressman my name is Faye Faye Lee I'm here today as the

co-founder and chairperson of AI for all a national nonprofit organization focusing on bringing hands-on experience in AI research to high school students

that have been traditionally underrepresented in the field of in the STEM fields such as Gers people of color and members of low-income communities

our program began at Stanford University in 2015 this year AI for all are expanded across North America to six university campuses I

often like to share with my students that there's nothing artificial about artificial intelligence it's inspired by people it's created by people and most

importantly it has an impact on people it's a powerful tool we're only just beginning to understand and that's a profound responsibility I'm here today

because the time has come to have an informed public conversation about that responsibility with proper guidance AI

will make life better but without it it stands to widen the wealth divide even further make technology even more exclusive and reinforce biases we've

spent generations trying to overcome this will be an ethical philosophical and humanistic challenge and it will require a diverse community of

contributors it's an approach I call human centered AI and it's made of of three pillars that I believe will help

ensure AI plays a positive role in the world the first is that the next generation of AI technology must reflect more of the qualities that make us human

deeper understanding of the contexts we rely on to make sense of the world progress on this front will make AI much better and understanding our needs but

will require deeper relationship between AI and fields like neuroscience cognitive science and the behavior sciences the second is the emphasis on

enhancing and augmenting human skills not replacing them machines are unlikely to replace nurses and doctors for example but machine learning assistive

technology diagnosis will help their job tremendously similar opportunities to intelligently augment human capabilities abound from health care to education

from manufacturing to agriculture finally AI must be guided by a concern for its impact we must address

challenges of machine biases security privacy as well as at the society level now is the time to prepare for the

effect of AI and loss ethics and even culture to put these ideas in practice governments academia and industry will have to work together

this will require better understanding of AI in all three branches of government AI is simply too important to be owned by private interests alone and publicly

funded research and education can provide a more transparent foundation for its development next academia has a unique opportunity to elevate our

understanding and development of this technology universities are a perfect environment for studying its effect on our world as well as supporting

cross-disciplinary next generation AI research finally businesses must develop a better balance between their responsibilities to shareholders and

their obligations to their users commercial AI products have the potential to change the world rapidly and the time has come to complement this

ambition with ethical socially conscious policies human center AI means keeping humans at the heart of this technologies development unfortunately

lack of diverse representation remains a crisis in AI women hold a fraction of high-tech positions and even fewer at

the executive level and this is even worse for people of color we have good reasons to worry about bias in our algorithms a lack of diversity among the

people developing these algorithms will be among its primary causes one of my favorite quotes comes from technology ethicist Shannon Baylor who says that

there is no independent machine values machine values are human values however autonomous our technology becomes its impact on the world will always be our

responsibility with the human centered approach we can make sure it's an impact

we'll be proud of thank you thank you and I now recognize myself four or five minutes for questions

I'm dr. Li there is a generally accepted potential for AI enabled teaching you know to a minimum you know providing a backup for traditional classroom

education so as a doctor I technology advances it seems reasonable to assume that your traditional education vocational training homeschooling and

even college coursework will need to change and adapt could you maybe comment about how education in general and for specific groups and individuals might be

transformed by AI and how how we can make that positive and really sort of have more of a democratization of Education particularly higher education and in stamin and science thank you for

the question of course I feel passionate about education so I want to address this question in from two dimensions one is how could we improve the education of

AI and stem in general to more students and and general community second is what can a I as a technology do to help education

itself and the first dimension as our work in AI for all we really believe that it's it's simultaneously a crisis

and an import important opportunity that we involve more people in the development of AI technology AI represents humanity has never created a

technology so similar or trying to resemble who we are and we need AI - we need technologists and leaders of

tomorrow to represent this technology so personally I think we need to democratize AI education to reach out to

more students of color girls women of traditionally underrepresented minority at AI for all for the past four years

we've already created a Lum Knight population of more than a hundred students and through their own community and outreach effort we have been

touching lives of more than 1,400 a youth ranging from middle schoolers to high schoolers in disseminating this AI knowledge and we need more of that in in higher education

the second dimension that I want to answer your question is yeah as a technology itself can help improve education itself in the machine learning

community I'm sure Greg you also agree with me that there's a increasing recognition of life the opportunity for lifelong learning using technology as a

assistive technology I have colleagues at Stanford who focuses on research in reinforcement learning and education how

to bring more technological assistance into the teaching and tutorial ization of education itself and I think this

could become a huge tool as I was saying to augment human teachers and human educators to so that our knowledge can

reach to more students and and wider community excellent and for other witnesses could you maybe comment

on how academic institutions and industry could work with government on a yacht so I you know for opening eyes

recommendation it's really about starting with measurement right to really start to understand what's happening in the field I think it's really about for example the study that we did showing the 300,000 times increase we need more of that we need to

understand where things are going where we are I think the government is a uniquely positioned to set some of the goalposts as well we've been pretty encouraged by seeing some of the work that is happening at Gao and also di UX

has had some success with this um so we think it's really about starting a low touch way for the dialogue to start happening because I think right now the dialogue is not happening to the extent

that it should thank you for the question yeah I do think that as the committees have pointed out this is a whole of society issue it's going to be government in partnership with the

private sector with academia to look at things I think there is room for thought about how to learn by doing creating internships and and ways to try

and solve real-world problems so that you have a mix of the classroom experience as well as making building you'll fail a lot of course with these things but learning in a safe

environment and then being able to grow expertise in that way thank you dr. Lee did you have anything you want to add to that also okay well

thank you and I now will recognize I'm mr. Lipinsky for five minutes thank you this is a fascinating topic and there's

one a try to move through some things quickly but I'll get get some good answers here it seems to me that mr.

Brockman you have a different view of how of a GI the possibility of a GI and how quickly can come then the GAO report is there

is there a reason for this is there something you think that Gao is missing and dr. Pearson could respond to that so

I don't know if I can comment directly on the report it's not being familiar enough with with other details in there but I can certainly comment on our perspective on AGI and its possibility and a lot of it really comes down to

rather than I think that there's been a lot of more emotion or intuition based argument and to your opening remarks you know I think that science-based reasoning in order to project what's happening this field is extremely

important and that's something that we've spent quite a lot of effort on since starting opening I almost three years ago and so looking at the barriers to progress as compute data algorithms

data is something that's changing very rapidly in terms of what data we can use the computation the power there is growing at a rate that we've just never seen over the course of this decade we're going to be talking you know I

think about ten orders of magnitude and that's something where if you were to compare that to the typical growth of compute something like Moore's Law that the over the the period where we saw

300,000 X increase in the past six years we would have only seen 12 X right that's that's a huge gap and that this is somewhere where we're sort of being projected into the future a lot faster than people realize now it doesn't mean

that it's going to happen soon it means that we can't rule it out it means that for the next five years as long as this Hardware growth is happening we're in a fog and it's hard to make confident projections and so my my position is

that we can't rule it out we know that this is you know we're talking about a technological revolution on the scale of the agricultural revolution something that could be so beneficial to everyone

in this in this world and if we aren't careful in terms of thinking ahead and trying to be prepared and really to be caught unaware thank you dr. Pearson do

you have a response and that sure I think and then with all respect for our Silicon Valley innovators who are upstarts and challenge the status quo I think it's great that that we have the

system the the key the key thing that we're seeing is the convergence of these technologies that was mentioned by my panelists of the exponential power and computing the biggest nature of data the

sophistication algorithms are all coming in but that said many folks in the community are mildly skeptical about the rate at which

general AI may come in this area because for several reasons one is just the way that we think about the problem now the code the super complexity that is

manifest in addressing the various Challenger looking at larger datasets and looking at all the facets of them it's much easier to say than to do and again I think a lot of the as you

pointed out the driving force here is the concern about general AI and and taking over the world kind of thing and it's just much harder to mimic human

intelligence especially an environment where intelligence isn't even really defined or understood and I think as dr. Li pointed out there were a lot of this is really about augmentation it's

something else we heard from our experts it wasn't a replacement of humans it was a how can we become better humans more functional humans and doing these things

so alive it just gets down short I'm sorry thank you I just want to throw out quickly the there have been very

different vastly different opinions and about the replacement of jobs and the disappearance of jobs and what the

impacts are going to be mr. Brockman what do you what do you think the impact will be so so I think that with new technologies in the short term we always

overestimate the degree to which they can they can make rapid change up I think in the long term the that that they do I think technology is changing that we've seen with things like the internet that there's been a lot of job

displacement both creation and and in destruction and I think AI will be will be no different I think the question of exactly which jobs and when I think we don't have enough information yet and I think that that's where measurement

really starts to come in so we view it as an open question in a very important one and survey and just say is a bottom line the nobody really knows the impact

on this and of course our experts were saying to no more we might need to be able to encourage let's for example our Bureau of Labor

six data type agency that out of the federal government to help provide more data or different data or things to help try and answer the question of what is the impact is this technology continues

to unfurl that said there's also a history of we need goes back and in tributed to Ned Ludd in the era of British industrialization and the

concern of destroying the machines for the concern about loss of jobs and yet and many times throughout history it's happened in in an array of technologies where net jobs actually increased it

just there were more sophisticated jobs they were toward higher value creation and more productivity so there is hope if this technology as well jerilyn will

allow I won't hear from dr. Lee I just want to say that technology inevitably in throughout human civilization has an impact to change the landscape of jobs

but it's really really critical like my fellow Pelin assets that we need to invest in the research of how to assess this change it's not a simple picture of

replacement especially when this technology has a much greater potential empower to augment it I just spent days in the hospital ICU with my mother in

the past couple of weeks and and and with my own healthcare and AI research you recognize that a nurse in a single shift is doing hundreds of different

tasks in our ICU unit where they're fighting for life and death for our patients and these are not a simple question of replacing jobs but creating better technology to assist them and to

to make their jobs better and make the lives better for everyone and that's what I hope we focused on using this technology thank you thank you dr. Lee

that's a wonderful example of really vividly explaining to us how that can be used because certainly as we're an aging population in this country that's a challenge we're all facing and so the

quality of life an improvement in each of those employees and nurses being able to do a better job thank you for for

lining that I now recognize mr. rubber Thank You Madame chair dr. Li is your mom okay we we hope that she is playing hope that she is okay thank you I'm here that means she's better her okay

otherwise we were gonna be missing two witnesses good she's watching me right now well good she's doing a great job you're doing excellent she's a proud mom and

that's some good medicine in and of itself right thank you so we're glad for that dr. Brockman you and your statement say

that your mission was to actually make sure their artificial intelligence benefited people and was better for the

most economically valuable work you remember that I so are it's a written statement yeah that's right so the definition of what AGI will be whether

created by us or anyone else but just that the milestone is a system that can outperform humans that let me read it to you real quick I'm Greg Bob and co-founder and nonprofit and develop our mission is to ensure that our artificial

general intelligence by which we mean highly autonomous systems that out that outperform humans at quote most

economically valuable works in quote benefits all humanity how would you define most economically valuable work

so so I think that again and first of all I just you know the the question of you know AGI is something that the whole field has been working towards for you

know really sense to be the beginning of the field fifty years ago I mean so the question of how to define it I think is something that is not entirely agreed-upon that our definition is this

and when we think of it we think of you think about things like starting companies or very very high intellectual work like that I and you know also to

things like I going and cleaning up I disaster sites or things that humans would be unable to do very well today okay well I noticed that in your disagreement that congressman Lipinski

referred to with the aid the report and you thought you call them Silicon Valley upstarts least you didn't call them young upstarts so that's an advantage thank you for doing

that but you're literally looking at a new industry that even though the ship bless you even though the ship is going to be

changing you're actually creating jobs for another industry and going back to dr. Lee's example with her mom in the eye you tell me how much the nurses do

how do you train for those jobs if it's moving as fast as you think it is yeah and so you know one thing I think is also very important is that I don't think that we have much ability to change the timeline to this technology I think that there are a lot of

stakeholders there are a lot of different pieces of the ecosystem and that what we do is we step back and we look at the trends and we say what's going to be possible when and so I think that the question of how to train again

that's going to be something we're not the only ones that that are going to have to help answer that question but I think that the place to start it really comes back to measurement right if we don't know what's coming if we can't

project well then we're going to be taken by surprise and so you know I think that there are going to be lots of jobs and already have been created job jobs that are surprising in terms of you think about with autonomous vehicles

that we need to label all this data we need to make sure that these systems are doing what we expect and that all of that that there's going to be humans that are going to help make these systems so we would all agree I hope and on this question for all three panelists

all three witnesses that the jobs are gonna create or well worth the transformation into all that technology doctor persons would you agree with that

I would agree with that let me give you a quick example if I may speaking with a former Secretary of Transportation recently just a simple example of Tollbooth collector's we have now a

system where the e-zpass you drive through and you have less of a work force there that did that could have had an impact at that time for a short

period on the number or loss of jobs for tobu collectors and yet it freed them up and enabled them to perhaps do other things that were needed large problems and mr. Brockman you were shaking your

head you would agree with that yeah absolutely I think the purpose of technology and improvement it's different people's lives so dr. Lee I see you shaking your head - yeah

absolutely in addition to the example persons provide I think deeply about the jobs that are currently dangerous and

harmful for humans from fighting fires to search a rescue to to you know natural disaster recovery not only we shouldn't put humans in harm's way if we

can avoid it but also we don't have enough help in these situations and there's this is where technology should be of tremendous help very quickly I'm out of time

just yes or no if we lose dominance in AI that puts us in a really bad spot and worldwide comparatives was your green

yes yes thank you yes I'm sure you'll bet thank you good question now I recognize mr. VC for five minutes thank

you madam chair we have heard about already from your testimony some of the advantages of AI and how it can help humankind how it can

help advance us as a nation and a country but as you know there are people also that have concerns about AI there's been a lot of sort of doomsday like

comparisons about AI and what the future of AI can actually mean to what extent do you think this scenario this sort of

you know worst-case scenario that a lot of people have pointed out about AI is actually something that we should be concerned about and and and and if and

if there is a legitimate concern what can we do to help establish a more ethical you know responsible way to

develop AI and and this is for anybody on the panel to answer so I think thinking about artificial general intelligence today is a little bit like thinking about the internet and maybe the late 50s all right if someone's to

describe to you what the internet was gonna be how it affect the world and the fact that all these weird things were gonna start happening grab this thing called uber which you're gonna be able to you just you'd be very confused to be very hard to understand what that would look like and the fact that Oh we'd

forget to put security in there and then we'd be paying for that for you know 30 years worth of trying to fix things and now imagine that that whole story which played out over really the of course the past 60 almost 70 years

now was going to play out in a much more compressed time scale and so that's the perspective that I have when it comes to artificial general intelligence is the fact that it can cause this rapid change and it's already hard for us to cope

with the changes that technology brings and so the question of is it going to be malicious actors is it going to be that the technology itself just wasn't built in a safe way or is it just that the deployment that who owns it and the

valleys that it's given aren't something that we're all very happy with all of those I think are real risks and again that's something that we want to start thinking about today thank you sir so I

I agree with that I think the key thing is being clear-eyed about what the risks actually are and not necessarily being driven by the entertaining and yet it's science fiction type narrative sometimes

on these things projecting or going to extremes and assuming far more than where we actually are in the technology so it's there are risks it's understanding the risks as they are and

they're always contextual risks risks in automated vehicles are going to be different than risks in this technology and financial services let's say so it's really working again symbiotically with the the community of practice and

identifying what are the things there what are the opportunities and there's going to be opportunities and then what undesirable things do we want to focus on and then optimize from there on on

how to deal with them thank you mr. bruckman in your testimony you reference a report outlining some malicious actors in this area could you sort of elaborate

on some of your findings in this area that's right so so opening I was a collaborator on this research report projecting not necessarily today what people are doing but looking forward what are some of the malicious

activities that people could use AI for and so that that report on let's see I I

think maybe maybe the most important things here you start thinking about things around information privacy the question of how do we actually ensure that these systems do with the operator intends

despite potential hacking you think about autonomous systems that are taking action on behalf of humans that are subvert it and whether again it's you

know that this report focuses on active action you think about autonomous vehicles and if the human hacker can go and take control of a fleet of those some of the bad things that could happen

and so and I think that the this report should really be viewed as we need to be thinking about these things today before these are a problem because a lot of these systems are going to be deployed in a large-scale way and if you're able

to subvert them then I we you know that all of the problems that we've seen to date are going to start having a very different flavor where it's not just privacy anymore as also systems that are deployed in the real world that are actually able to to affect our own

well-being thank you madam chair yield

back you and I know thank you very much

madam chairman this as in all advances in technology it can be seen as a of the

great hope for making things better or the new idea that there might be new dangers involved and or that new

technologies will help certain people's but be very damaging to others and I think that where that fear would be most

recognisable as in terms of employment and a how in a free society people earn a living and are we talking about here

about the development of technology that will help you know get the tedious and

remedial or the lower skilled jobs that are are really not really that can be done you know by machine or are we

talking about a loss of employment by machines that are design to really perform better than human

beings perform in high-level jobs what are we talking about you okay so I can I still gonna use healthcare as example

because I'm familiar with that area of research so if you look at recent studies by McKinsey and other

institutions on employment and AI there is a recognition that we need to talk a little more nuanced than just a entire

job but the tasks under each job the technology has a potential to change the nature of different tasks again for

example take take nurse a job of a nurse as an example it no matter how rapidly we develop the technology in the most

optimistic assistant it's very hard to imagine that entire profession of nurse nursing would be replaced yet within the nursing jobs there are many

opportunities that certain tasks can be assisted by AI technology for example a simple one that costs a lot of time and

effort in nursing jobs is charting our nurses in our again ICU rooms or patient room spends a lot of time typing and charting into a system into a computer

while that's time away from patients and and other more critical care so these are the kind of tasks under a bigger job

description that we can hope to use technology to assist in and augment so we talked about robots here or a box

that thinks and is able to make decisions for us so air technology is a technology of many different aspects

it's not just robot in this particular case for example natural language understanding the speech recognition well possibly in the in the form of a

voice assistant would help charting but maybe delivering of simple tools in fact on the fact fluor will be in the form of a small

simple delivery robot so there are different forms of machine we have there there are many dangerous jobs that I

could see that we don't we'd prefer not having human life put at risk in order to accomplish the goal and for example

at nuclear power plants we would it would be a wondrous thing to have a robotic response to something that could

cause great damage to the overall community but would kill somebody if they actually went in to try to solve a problem and I understand that and also

possibly with communicable diseases where people need to be treated but you're putting people at great risk for

doing that however with that said when people are seeking profit in a free and open society I would hate to think that

we're putting out of work people with lower skills and we need the dignity of work and and and of earning your own way

once we know now what when you take that away it really has a major impact negative impact on people's lives so I want to thank you all for giving us a

better understanding of what we're facing on this and let's hope that we can develop this technology in a way that helps the widest variety of people

and not just perhaps a small group that will they keep their jobs and keep the money so thank you very much thank you

and I now recognize miss bond amici for five minutes thank you so much thank you to our witnesses first I want to note that our nation has some of the best scientists and researchers and engineers

in the world but without stronger investments in research and development especially sort of long-term foundational research we risk falling behind especially in this

important area I hope the research continues to acknowledge the socio-economic aspects as well of integrating AI in technologies in my home state at the University of Oregon

we have their urbanism next Center they're doing some great work bringing together into interdisciplinary perspectives including planning and architecture and engineering and urban

design and public administration with public private and academic sectors to discuss how leveraging technology will shape the future of our communities their research has been talking about

emerging technologies like autonomous vehicles and the implications for equity health the economy and the environment and governance dr. Pearson

can you discuss the value of establishing this type of partnership between industry academia and the private sector to help especially identify and address some of the

consequences intended and unintended of AIS that becomes more prevalent and I I do have a couple more questions Charlotte so quickly the short answer is yes are our experts and and what we're

seeing is the value in public-private partnerships because again it would be a mistake to look at this technology and sort of isolated stovepipes and it would need to be an integrated approach to

things the federal government having its various roles but key like you're mentioning a University of Oregon key academic and research questions there's many many things to research and questions to answer in then of course

industry which has an incredible amount of innovation and thinking and power to drive things forward thank you dr. Lee I have a couple questions do you discuss the labor disruption and I know that's brought up

a couple of times and the need for retraining we really have sort of a dual skills gap issue here because we want to make sure there are enough people who have the education needed for the AI

industries but we also are talking about the workers like you mentioned the the workers in tollbooths who will be displaced but with the rapid development of technologies and the changes in this

field what knowledge and skills are the most important for a workforce capable of addressing the opportunities and the barriers out to the development I serve on the education and Workforce Committee

and this is a real the important issue is how do we educate people to be prepared for such rapid rapid changes so AI is fundamentally a

scientific and engineering discipline and - as an educator I really believe in more investment in STEM education from

early age we look at in our experience at AI for all when we invited these high school students in the age of 14 15 16 -

to participate in AI research their capabilities and and-and-and potentials just just amazes me we have high school students who have worked in my lab and

winning best paper award at this country's best AI academic conferences and so so I believe passionately that

STEM education is critical for the future for preparing AI thank you and everyone on this committee knows I always talk about steam because I'm a big believer in educating both halves of

the brain and students you have arts education tend to be more creative and innovative I also dr. Lee in your testimony you talked about how AI engineers need to

work with neuroscientists and cognitive scientists to help AI systems develop a more human feel now I know dr. carbonyl is not here today but I noted in his

testimony he wrote AI is the ability to create machines who perform tasks normally associated with human intelligence I'm sure that was an

intentional choice to humanize the machine but I wanted to ask you dr. Lee about he's not here to explain but I have no doubt that was intentional in

her testimony you talked about the laws that codify ethics how how is this going to be done can you go into more depth about how would how would these laws be done

who would determine what is ethical that would be a combination of industry government it determine determine estándares how was how are we going to set the stage for an ethical development

of AI yes so so thank you for the question I think for technology as impactful as a is to human society it's critical that

we have ethical guidelines and different institutions from government to academia to to industry will have to participate

in this dialogue together and also by themselves are they already doing that though you say that they'll have to but where is somebody convening all of this to make sure that there are so there are

efforts I'm sure a great can add to that the industries in Silicon Valley we're seeing companies starting to roll out a is achill principles and responsible AI

practices in academia we see that ethicists and and social scientists coming together with technologists

holding seminars symposiums classes to discuss the ethical impact of AI and hopefully government will participate in this and and and support and invest in

this kind of efforts thank you I see my time is expired thank you madam chair you're back Oh mr. chairman thank you I thank the

gentlelady the gentlelady from Arizona is recognized for five minutes Thank You mr. chair I want to thank the testifiers today very interesting

subject and something that kind of spurs the imagination about science fiction shows and those type of things I do have

a question on what countries are the major players in AI and where does the u.s. rank in competition with them and

u.s. rank in competition with them and that's to any panelists or all panelists so you know today I think that the u.s.

actually ranks I possibly top of the list um you know I think that there are lots of other countries that are investing very heavily you know China is investing heavily lots of countries in Europe are investing heavily that I you

know deep mind is a subsidiary of a US company but located in in in London and I think that you know it's very clear that AI is going to be something with global impacts and I think the more that we can understand what's happening

everywhere and figure out how we can coordinate on safety and ethics in particular the better it's going to go yes I thank you for the question I think wherever there's large amounts of

computing large amounts of data and a strong desire to innovate and and and continue to develop again in this sort of fourth Industrial Revolution that we're moving on then yeah it drives

toward certainly China and then our allies and colleagues in Western Europe developed worlds

thank you and is there did you want to answer if I could just add that you know the most important thing to continue to lead in the field it's really about the

talent and right now we're doing a great job of bringing all the talent in at opening I we have a very wide mix of national backgrounds and origins I think as long as we can keep that up that will

be in very good shape thank you and mr. chair I have one more question and that is what steps I think this has been

asked in different ways before but what steps are we guarding against espionage from let's say you said China is

involved in this and that's basically my question espionage hacking those type of things what guidelines are currently

taking place and who's preventing this is that the private companies themselves government involved thank you so one thing that's very atypical about this

field is because it really grew out of an academic eye a few very small number of academic labs that the over over arching ethos in the field is actually

to publish and so all of the core research and development is actually being shared pretty widely and so I think that as we're starting to build these more powerful systems and this is one of the parts of of our charter that

we need to start thinking about safety and and keeping you know think about things that should not be shared and so I think that this is a new muscle that's being built it's right now kind of up to

each company and I think that that's something that we're all starting to develop but I think having a dialogue around what what's okay to share and what things are kind of too powerful and and should be kept private that's that's

just the dialogue is starting now and certainly IP intellectual property protection is a critical issue I think of a one former director of the National Security Agency

mentioned that the we're at the time it was unprecedented theft of US intellectual property at that time just because of the it's the blessing and curse of the internet the blessing it's

it's open and the curses it's open and so AI is going to I think be in that that category in terms of what's being done in terms of cybersecurity it is something our experts pointed out and

said it is an issue as this committee well knows it's easier said than done and who has jurisdictions in the u.s.

federalist system about particularly the private company and protection of that the role the federal government versus the company itself in an era where as I think mr. Rothman's point out it was

sort of the big data era where data are the new oil yet we want to be open at the same time so that we can innovate so managing that dialectical tension is going to be a critical issue and there

is no easy answer Thank You mr. chair I yield back she'll recognize Miss su for five minutes Thank You mr. chair and I want to thank the witnesses for this

extremely informative and important conversation that we're having here today I hail from the state of Connecticut where we see a lot of

innovation at UConn at Yale at lots of spin-offs on the sort of narrow AI question but I think for us really the issue is more about that general AI and

in mr. Brockman your discussion of the advances which makes Moore's law looked puny in comparison is really where I want to take this conversation about dr.

Lee years your discussion which i think is incredibly important about diversity we saw what happened to Lehman Brothers by not being diverse I am extremely concerned about what the implications

are for teaching a as it were if it's garbage in it's going to be garbage out if it's a very narrow set of parameters and thought patterns and life

experiences that go into AI we will get very narrow results out so first I want to just talk get your thoughts on that and the second is on this broader

ethical question we've looked for many years I remember back when I was a young lawyer working on bioethical issues the Hastings Center got created to begin to look at these issues this committees

been grappling with CRISPR and the implications of CRISPR I think about this being very similar that AI has many similar implications for ethical input

so if you can opine on both of those questions and recognize we've got two you know two minutes three minutes left about both the ethical whether we need

centers to really bring in ethicist as well as technologists and then the importance of diversity on the technology side so that we get the full

range of human experience represented as we're exciting our exciting new entry into this fourth gen revolution thank you yes

in fact when just now thank you for asking that question just now when someone is using the term doomsday scenario to me I think if we wake up 20 years from now whatever years and we see

the lack of diversity in our technology and leaders and and practitioners that would be my doomsday scenario so it's so important and

critical to have diversity for the following three reasons like you mentioned one is shir jobs that we're talking about this is a technology that

could have potential to create jobs and and and and improve quality of life and we need all talents to participate in that second is innovation and creativity

like you mentioned in Connecticut and other places we need that kind of broad talent to adding the the force of AI development and a third is really

justice and moral and moral values that if we do not have this wide representation of humanity representing

the development of this technology we could have face recognition algorithms that are more accurate in recognizing a male white male faces and these are we

could have dangers of our biased algorithms making unfair long application decisions you know there are meaning potential pitfalls of a

technology that's biased and not diverse enough which brings us to this conversation doubt dialogue of ethics

and ethical AI you're right I'm previous disciplines like nuclear physics like biology have shown us the importance of

this I don't know if there is a single recipe but I think the need for four centers institutions boards and

government committees are all potential ways to create an openness this dialogue and and again we're starting to see that but I think you're totally right it's

critical issues I'm so I agree completely with my fellow witness so diversity is crucial to success here also actually so we have a program called opening high scholars where we

brought in a number of people from underrepresented backgrounds into the into the field and provide mentorship and that they're working on projects and spinning up one thing that we found that I think is very

encouraging is actually very easy to take people who do not have any AI or machine learning background and to make them into extremely productive first-class researchers and engineers

very quickly and that's you know one benefit of this technology being so new and nascent is that in some ways that we're all discovering as we go along to so becoming an expert there just isn't

that high of a bar but so I think that did everyone putting effort in the places where the expertise is I think it's on them to make sure that they're also bringing in the rest of the rest of the world on the ethical front that's

really core to my organization that's that's the reason we exist that we do you think that you know for example when it comes to the benefits of who owns this technology who who gets in where do the dollars go we think it belongs to everyone and so one of the reasons that

I'm here is because I think that this shouldn't be a decision that's made just in Silicon Valley I don't think that the question of the ethics and how this is going to work should be in the hands solely of people like me I think that

it's really important to have a dialogue and again that's something where you know I hope that that will be one of the outcomes of this hearing thank you very

much Jilla now recognizes mr. McNerney well I think the chair for holding this and the ranking member and I think the witness is a really very interesting

testimony and diverse in its own right one of the things I think that's important here is with this committee is how how does the government react to AI

do we need to create a specific agency does that agency report to Congress sort of the administration those sorts of things I think are very important dr. Brookman

you said I think one of the most important things was that we need a measure of AI progress do you have a model or some description of what that

would look like uh yes I do thank you for the question and so first of all I don't think that we need to create new agencies for this I think that existing agencies are well set up for this and I was actually very encouraging here that

people are talking about giving NIST a remit to think about these problems again Gao and di UX are already starting to work on this for

example di UX had a satellite satellite imagery data set hosted a public competition the kind of thing that we think would be great for government to do as well is to have standardized environments where academics and private

sector can test robotic approaches setting up competitions towards specific problems that various agencies and departments want to be solved all of those I think can be done without any new agency and I think that that's

something that you can both get benefits directly to the relevant agencies also understand the field and also start to build ties between private sector and

public sector I'm one of the founders of the grid innovation caucus what are the most likely areas we'll see positive benefits to the grid to electric grid

stability and resiliency who would be the best answer mr. Pearson's sure thank you for the question Minh of the ways of

gia has done a good deal of work on this issue but it's just protection of the electrical grid in the cybersecurity dimension so is one of our scenarios or

profiles that we did in this in this report what are experts in what folks were saying and again the at the based on the leadership of this committee and the importance of cyber is that it's a

without which nothing AI is going to be a part of cyber moving forward and so protection of the grid and the cyber dimension is there also I think as the chairman mentioned earlier the word

optimization so how we opt optimize things and how algorithms might be able to compute and find Optimum's faster and better than humans is an opportunity for

grid management and production of things so a AEI is also going to be used as a cyber weapon against infrastructures or potentially uses a weapon is that right

there there are concerns now when you look at a broad definition of AI and you look at BOTS now that are attacking networks and doing distributed what are DDoS or distribute denial of service

attacks and things like that that exists now you could unfortunately in the black hat assumption you're going to assume that as ai becomes more sophisticated and the

white hats ends so - unfortunately the black hat side of things the bad guys are going to also become more sophisticated and so it's going to be the cat and mouse game I think moving

forward another question for you dr. Pearson's in your testimony you mentioned that there's considerable uncertainty in the jobs impact of AMA

yes what would you do to improve that situation our experts were encouraging specific data collected on this again we

have important federal agencies like BLS Bureau of Labor Statistics of that that work on these issues what's going on in the labor market for example and it may

just be a an update to what we collect what questions we ask as a government how we provide that data which is course very important to our understanding of

unemployment metrics and so on so they're economists that have thoughts about this that we had some input on that there's no easy answer at this time but the idea that there is an existing

agency doing that sort of thing is there the key question is how could we ask more or better questions on this particular issue on artificial systems

thank you dr. Lee you gave three conditions for progress in AI being positive do you see any acceptance or

general wide acceptance of those conditions how can we spread the word of that so that the industry is aware of them and the government is aware of them and that they follow those sorts of

guidelines thank you for asking yeah I would love to spread the word so um I think I do see the the emergence of

efforts in all three conditions the first one is about more interdisciplinary approach to AI and ranging from universities to in to

industry we see the recognition of neuroscience cognitive science to cross pollinate with AI research I want to add

we're all very excited by this technology but as a scientist and very humbled by how nascent the science is it's owning a

size of 60 years old compared to traditionally classic science that's making human lives better everyday physics chemistry biology there is a

long long way to go for AI to realize its full potential to help people so so that recognition really is important and we need to get more research and

cross-disciplinary research into that second is the augmenting human and again a lot of academic research as far as

industry startup efforts are looking at assistive technology from disability to you know helping humans and the third is what many of us focus on today is the

social impact from studying it to having a dialogue to having to working together through different industry and government agencies so all three are the

elements of human Center a I approach and I see that happening more and more thank you chair now recognizes Germany

York nope jaren I recognize the gentleman it's not from New York mr. Palmer Thank You mr. chairman I'd like

to know if AI can help people who geography challenged gentlemen time has expired

I requested that question and response be removed from the record I do have some questions in my district we have the national computer forensics

Institute which deals with cybercrime and what I'm wondering about is with the

emergence of an evolution of AI how does it what are we putting in place because of the potential that the debt creates for committing crime and for solving

crime doctor persons do you have any thoughts on that well certainly in one of the areas we did thank you for the question one of the areas we did look at in general was just criminal justice

and just the the the risks that are there in terms of the social risk making sure the the scales are balanced exactly as they ought to be that justice is blind and so on it was was the focus of

that however think in terms of the criminal forensics AI could be a tool that helps us out what happened you know in a retrospective sentence what happened but again it's an augmentation

that's helping the forensic analysts who would know what things look like and the algorithm would need to in the machine learning sense of things would need to learn what the risks might be going

forward so that you perhaps could identify things more proactively and perhaps a near or at real-time so that's the the opportunity for this again AI as

a tool in cyber was a key message we heard moving forward so today you know we're already starting to see some of

the security problems with the methods that were creating for example that there's a new class of attack called adversarial impuls where researchers are able to craft a like a physical patch

that you could print out and put on any object they'll make a computer vision system think that it's whatever object you want it to be so you can put that on a stop sign and confuse a self-driving car for example so these sorts of ways

of subverting these powerful systems is something we're going to have to solve and gonna have to work on just like we've been working on computer security for more conventional systems and I think that the way to think about if you

could successfully build and deploy an AGI what that would look like in many ways it's kind of like the Internet in terms of being very deeply integrated in people's lives but also having this increasing amount of autonomy and

representation and taking actions on people's behalf and so you'll have kind of this question of how do you make sure you know first of all that's something that could be great for security if

these systems are well built and have safety in their core and are very hard to subvert but also if it's possible for people to hack them or to cause them to do things that are not aligned with the

value of the operator then I think that you can start having very large-scale disruption it also concerns me in the context of it was announced a couple of

weeks ago that that united states plans to form a space core we know that China has been very aggressive in militarizing space if you

have any thoughts on that discussion of how it artificial intelligence will be used in regard to to space communication

systems that are highly vulnerable already I don't think that there's some additional vulnerability that would be created and he thoughts on that and that

any one of the three of the panelists yes sir I so in terms of the the risk in space obviously one of the key concerns

for AI is weaponization in which I think is is as part of that and so much less the space domain or any other one and so I know our Defense Department has key leadership thinking on this and working

strategically on how do we operate in an environment where we have to assume there's going to be the adversary might not operate in the ethical framework that we do and to defeat that but

there's there's no simple answer at this time other than our Defense Department is thinking about it and working on it and now he's not here

obviously to testify but in dr. carbonyls testimony he made a statement that we need to produce more AR researchers especially more US citizen

or permanent resident AI researchers and I think that kind of plays into that that issue of how do we deal with AI in

space that's one of the reasons why I've been pushing for a college program like an ROTC program to recruit people into the space Corps in these areas start

identifying students when they're maybe even in junior high and scholarship them and through college to get them in into these positions any thoughts on that

I'll just answer quickly and just say I think as dr. Lee's I think elegantly pointed out before this is really an interdisciplinary thing I think there's going to be a need for sort of the stem of steam specialists that

particularly focus on this but I think any particular vocation is going to be impacted in one way or the other just like you could imagine rewinding a couple decades or a few decades I'll date myself but when the advent of the

personal computer of the PC coming in and how that affected now we walk into dating vocation and someone's using a PC or something like that and it's not unusual but at the time you had to learn

how to augment yourself or your task with that and if I may mr. chairman just had this final thought is we've had to

deal with with some major hacks federal government systems that they're hacked and and what we're faced with we're competing with the private sector for the best and brightest in terms of cyber

security we're going to find ourselves in the same situation with AI experts the truly skilled people and that's why

I'm suggesting that we may need to start thinking about how do we recruit these people and get them in as employees of the federal government and that's that

was my thoughts on setting up a an ROTC type program where we recruit people in which scholarship on whether it's for cyber security or for AI and with a you

know four or five year commitment to work for the federal government because there's going to be tremendous competition and the federal government has a very difficult time competing for

those type people so with that mr. Chairman I yield back now the chair recognizes the gentleman from New York it's okay we're patient I thank our

respective chairs and ranking members for today's very informative hearing and welcome and thanks to our witnesses I'm proud to represent New York's 20th congressional district where our

universities are leading the way and artificial intelligence research and education initiatives SUNY Polytechnic Institute is currently the home of groundbreaking research developing

neuromorphic circuits which could be used for deep learning such as pattern recognition but are also useful for AI or machine learning in addition the Institute has established an ongoing

research program unrest of memory devices Ressler Polytechnic Institute RPI is pushing the boundaries of artificial intelligence in a few different areas in the healthcare

fronts RPI is focusing on improving people's lives and patient outcomes by collaborating with Albany Medical Center to improve the performance of their emergency department by using AI and

analytics to reduce the reoccurrence of costly ER visits by patients and RPI researchers are also collaborating with IBM to use the Watson computing platform

to help people with pre-diabetes avoid developing the disease in our fight to combat climate change and protect our environment researchers at RPI and Earth and environmental science are working

with computer science and math and machine learning researchers to apply cutting-edge AI to climate issues in the education space RPI is exploring new

ways to use AI to improve teaching as well as new approaches to teaching AI and data sent the science to every student at RPI with all that being said

they're tremendous universities across our country that are excelling in AI research and education and what are some of the keys to helping AI institutions

like them to excel what do we need to do it would be the most important that's to any one of our panelists so thank you

for asking that question I think just like we recognize AI really is such a widespread technology that I

think one thing to recognize is that it is still so critical to support basic science research and education in our universities this technology is far from

being done of course the industry is making tremendous investment and an effort into AI but it's a nascent science it's a nascent technology we

have many unanswered questions including the socially relevant AI including AI for good including AI for education

health care and many other areas so one of the biggest things I see would be us into the basic science research into our

universities and encouraging more students thinking in interdisciplinary terms taking courses you know they can

be stem students team students yeah it's not just for engineers and scientists it could be for students with policy making mind for students with law interests and

and so on so so I hope to see university universities participating in this in a tremendous weight like meaning great

schools in New York State thank you dr. person sir mr. Brockman either so sorry I agree with dr. Lee but I also point out that I think it is also becoming

increasingly hard to truly compete as an academic institution I because if you look at what's happening industry right now is actually doing fundamental research it's very different from most

scientific fields and the salary disparity between what you can get at one of these industrial labs versus what you can get in academia it's it's very very large there's a second piece which is in order to do the research you need

access to massive computational resources and for example the work that we just did I with with this this you know come big game breakthrough that required basically a giant cluster of

you know something around ten thousand machines and that that's something where in an academic setting it's not clear how you can access to those resources and so I think for the playing field to

still be accessible I think that there needs to be some story for how people in academic institutions can get access to that and I think that the question of you know where is the best research going to be done and where the best

people going to be I think that's something that it's you know playing out right now I think in industries favor but it's not necessary not necessarily set in stone thank you dr. persons yes

sir thank you for the question and I would just add to my fellow panelists the fact that our experts had said that real-world test beds are important to this you don't know what you don't know

so not only in addition to adding access to data but being able to test and do things these one thing for sure and I learned in fact from open AI that a lot of the times these things come out with

surprising results and so that's the whole reason of creating safe environments to try things out and de-risk those technologies and that's something that I think is going to be

important to to enable that basic research to have an avenue to perhaps move up the technology maturity scale possibly into the market and certainly hopefully to solve critical complex

real-world problems thank you very important if mr. chair I yield back giman now recognizes I'm the chair now retina Jim Illinois Thank You mr. chairman and thank you for coming to

testify today you know I've been interested in artificial intelligence for quite a long time back in the 1990s in working in particle physics we were using neural network classifiers to have

a look at trying to classify particle physics interactions and when I couldn't stand it during the government shutdown and not so long ago I went and downloaded tensorflow and worked through

the part of the tutorial on it and you know the algorithms are not so different than what we were using back in the 1990s but the computing power in difference is breathtaking and I very

much resonated with your comments on on the the huge increase in dedicated computer power for for deep learning and similar and that is likely to be

transformative given the recent and so that you know we have to think through that because even with no new brilliant ideas on algorithms there's going to be

a huge leap forward so thank you for that that's a key observation here you know else in Congress I'm the co-chair of the New Democrats coalition of future

of work task force where we have been trying to think through what this means for the workplace of the future and so I'd like to them mr. chairman I'd like to submit for the record white paper

entitled closing the skills and opportunity gaps without objection that objection so ordered thank you and I will be asking for the record if you could have a look at this

and see if you know how what sort of coverage you think this document has for the near term policy responses because it's you know this is coming at us I think

faster than a lot of people in politics really understand and also I will be asking for the record I guess you may not have to respond right now I'm where

the best sources of information on how quickly this will be coming at us you know there are conferences here and there but you you attend and your friends attend a lot of them I'd be

interested in where you think you really come together to get the techno experts the economic experts you know the labor economists people like that all in the same room I think it's um it's it's

something we should be putting more effort into on another tack I've been very involved in Congress in trying to resurrect something called the office of Technology Assessment you know what the

Jo did here is very good which is to bring we had a conference of the experts and you brought in a good set of experts and a year later now we are getting a report on this and you know you need

more bandwidth in Congress than that just you know on all technological issues but this is a perfect example a year old group of experts and then AI

you know as those are opinions that are sort of dated a little bit even a year in the past and so the office of Technology Assessment for decades have

provided immediate high bandwidth advice to Congress on all sorts of technological issues and so we're coming closer and closer every year in getting

it refunded after it was defunded in the 1990s and so um so I think well and to ask you a question here is there anyone

on the panel who thinks that Congress has enough technological capacity as it currently stands to deal with issues

like this so I can answer them ya know it's you know it's a it's a huge problem and it's it's been aggravated by the fact that people have decided in

their wisdom to cut back on the size and salaries available for congressional staff one of my the previous members who talked about here talked about that difficulty the federal government will

have in getting real professionals top-of-the-line professionals in here and you know we're seeing members of Congress are willing to do anything but give them the salaries that there will

be necessary to actually compete for those jobs let's see I am now - let's see Oh mr. Brockman you had um your I

wouldn't advocate everyone have a look at the reference 5 in which is your malicious use of AI your reference 5 in your testimony which I spent I stayed up

way too late last night reading that and it is real along the same lines members of Congress have access to the classified version of National Academies

of science study on the implication of of autonomous drones for and this is something that I think you know has to

be understood by the military we're about to mark up a military authorization bill an appropriations bill that is spending way too much money

fighting the last war and not enough of fighting the Wars of the future and then finally um director Lee um

the in in the educational aspects of this one thing I struggle for I guess if you look through the bios of people who are the heroes of artificial intelligence they you know tend to come

from physics math places like that and in theoretical physics or mathematics a huge fraction of the progress comes from a tiny fraction of people it's just a historical truth and I was wondering is

a I'd like that are they you know are there a small number of heroes that really do most of the work and everyone

else sort of fills in the thing like I said dr. frost her AI is a very nascent

field so even though it is collecting a lot of in soozee azzam as worldwide so societally as a science it's still very young and

as a young science it starts from a few people as a I was also trained as a physics major and I think about early

days of Newtonian physics and that was a smallish group of people as well I mean it's it would be too much to compare

directly but what I really do wanna say is that we might be in the early even pre Newtonian days of AI we are still

developing this so so so that the the number of people are still small having said that there are many many people who have contributed to AI their names might

not have made it to the news to the blocks to the tweets but these are the names that as students and experts of this field we we we remember them and

and I want to say many of them are members of them underrepresented minority group there are many women in the first generation of AI experts so

when I was two or three clicks down in the the references cited by your testimony and you look at the papers there and the author lists it's pretty clear that our dominance in AI is due to

immigrants okay and and act early I suspect you might not have come to this country under the conditions that are now being proposed by our president and so I won't ask you to answer there but it's but it's important when we talk

about what it is that makes this country dominant and things like AI it is immigrants okay and I'll just leave it that I guess my time is up thank you gentlemen

I thank the witnesses for their testimony and the members for their questions the right to remain open for two weeks for additional written comments or written questions from members hearings adjourned [Music]

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