Congressional European Parliamentary Initiative
While the Congressional European Parliamentary Initiative (CEPI) fellowship has traditionally convened in Washington, D.C., Brussels, Berlin, and elsewhere, given the current circumstances, the 2020 program shifted to a virtual fellowship. In lieu of in-person meetings, fellows participated in virtual meetings, debates, and social hours, partnered on transatlantic writing components, and contributed to other digital content.
In virtual meetings on both sides of the Atlantic, CEPI participants engaged with diverse, high-level stakeholders in the federal government, the U.S. Congress, industry, and civil society to discuss politics and policymaking related to artificial intelligence and machine learning. Fellows also engaged with representatives of the European Commission and Parliament, the German federal government and Bundestag, and a wide range of European industry and civil society stakeholders. The 2020 virtual program kicked off in June and concluded in November.
These combined experiences helped provide participants with tools to enhance policy formulation, deepen participants’ understanding of transatlantic legislative processes, and helped build bridges to safeguard the long-standing friendship between the European Union and United States.
Lashrecse D. Aird
Delegate Lashrecse D. Aird was sworn in January 2016 to represent the 63rd House District, which includes all of the City of Petersburg, all of Dinwiddie County and parts of Chesterfield County. She holds the special distinction of being the youngest woman ever elected to the Virginia House of Delegates.
Delegate Aird serves on the General Laws; Health, Welfare and Institutions; and Appropriations committees. Out of session, she serves on the joint subcommittees on Tax Preferences and Local Governments in Fiscal Distress. She was recently appointed to Virginia Tobacco Region Revitalization Commission, which awards grants that support job creation, education and a variety of projects in tobacco-dependent communities.
Delegate Aird earned her undergraduate degree from Virginia State University in 2008. She is a graduate of the University of Virginia’s Sorensen Political Leadership Program; a graduate of the American Council on Education Virginia Network for Women in Higher Education’s Senior Leadership Seminar and a graduate of Virginia Commonwealth University’s Minority Political Leadership Institute. In addition, she was awarded an honorary Doctorate of Humane Letters, from Virginia State University in 2019.
In addition, she is a member of the Petersburg Alumnae Chapter of Delta Sigma Theta Sorority, Inc., the James House Board of Directors, Sports Backers Board of Directors and is a member of the Responsible Leaders Network for the BMW Foundation Herbert Quandt.
What’s your favorite written piece on AI? Race After Technology: Abolitionist Tools for the New Jim Code, Ruha Benjamin
How do you define AI in a few sentences? The ghost in the machine.
What’s the most pressing policy we need to change or develop surrounding AI? Accountability for algorithmic bias...
What is the most difficult part of working at the intersection of technology and policy?
The technology is actively evolving and so much continues to be misunderstood by policymakers, making it difficult to regulate.
What’s your favorite AI lecture/podcast/video? The Future of Life Institute Podcast, multiple episodes.
State Senator Raumesh Akbari was elected to the Tennessee State Senate in fall of 2018 after serving as a State Representative since 2013. Senator Akbari is a member of the Senate Commerce and Labor Committee, the Senate Energy, Agriculture and Natural Resources Committee, the Senate Ethics Committee and serves as 2nd Vice-Chair of the Senate Education Committee.
A graduate of Washington University and the Saint Louis University School of Law, Senator Akbari is currently chair of the Senate Democratic Caucus; former chair of the Tennessee Black Caucus of State Legislators; treasurer of the National Black Caucus of State Legislators (NBCSL); and financial secretary of N.O.B.E.L., the National Organization of Black Elected Legislative Women. She is the recipient of several honors and awards from the Council of State Governments and its affiliated Southern Leadership Conference; Leadership Memphis; Leadership Tennessee; the National Council of State Legislatures; the State Legislative Leaders Foundation; NBCSL; N.O.B.E.L.; the National Juvenile Justice Network; and Governing Magazine’s Governing Institute for outstanding appointed or elected women officials.
She has represented Tennessee by participating in programs in Canada, Australia and China, and most recently, by being one of the invited participants in the Transatlantic Inclusion Leaders Network (TILN), a network of young elected leaders representing 21st century policymakers. A program of the German Marshall Fund of the United States, TILN fosters collaboration on issues and policy affecting people around the world. She was invited by the Democratic National Committee to speak before the 2016 Democratic National Convention in Philadelphia.
How do you define AI in a few sentences? AI is technically defined as the intellect displayed by machines, but rapid developments in machine learning technology have left that definition in the dust. From Yan Shi’s gift to King Mu in the 10th century to Jane Robinson’s advancements in natural language processing in the late 20th century, the theoretical and practical applications of AI has opened a new frontier in scientific discovery. In some ways, this technology has surpassed human ability in specific tests. OpenAI's GPT-3 is an example of a machine that can create language that is almost indiscernible from our own. This leads to one of my definitions of AI; a machine that, for specific tasks, can rapidly achieve tasks at a similar or higher level than humans. As Andrew Ng simply said, AI is the new electricity.
How can we envision or describe data in a sentence or two? I see data as the rapid analysis of isolated information points in order to reach an actionable conclusion or to explain phenomena. Data will be one of the highest valued commodities as AI continues to progress.
What’s your favorite quarantine song? Recently, Georgia on My Mind-- Ray Charles
What’s your go-to quarantine drink? Coffee with a shot of espresso and cream. And Diet Coke. Caffeine is a recurring theme.
Yilmaz Akkoyun is a policy advisor to Steffen Bilger, German Federal Parliament member and State Secretary in the German Federal Ministry of Transport and Digital Infrastructure. Yilmaz has more than five years of work experience in the German government, its parliament and international organizations. As a Julius Blocker Scholar, he graduated within the Global Public Policy Network’s dual degree program from Columbia University with a master’s degree in public administration specializing in advanced policy and economic analysis, as well as a master’s degree in public policy from the Hertie School of Governance in Berlin. Before joining the office of Mr. Bilger, Yilmaz worked as a graduate consultant for the United Nations Capital Development Fund in New York City and Kampala. Prior to that and during his studies in Berlin, he worked at the German Federal Foreign Office in the German foreign service. As a Sustainable Development Goals (SDG) Professional Certificate Fellow, he is passionate about cross-sector collaborations and digital infrastructure policy.
What’s your favorite written piece on AI? The Singularity is Near: When Humans Transcend Biology written by Ray Kurzweil.
What’s your favorite AI lecture/podcast/video? Artificial Intelligence with Lex Fridman, MIT AI.
Are you optimistic or pessimistic about the effects of AI on society? Why? Between utopia and dystopia, many more scenarios are possible. At stake is nothing less than what kind of society we aim to live in and how we experience humanity in the 21st century.
I am optimistic we will use AI to improve the state of the world. On the one hand, we can use AI to further reduce global poverty as well as diseases and offer better education to almost every student on our planet. On the other hand, AI and machine learning can also be used to increasingly concentrate power, wealth and leaving many people worse off. It is our mission to ensure the technology advancement matches our values. I am convinced that AI will, above all, strengthen and improve the effectiveness of human activities – but will not replace them. The economic potential of AI is huge - but we also have to lift it.
What’s your go-to quarantine drink? Double Espresso Macchiato.
What’s a startup that you think is really cool right now? Lilium, the Munich-based startup making one of the world’s first all-electric vertical takeoff and landing (VTOL) jets.
Philip Boucher is a policy analyst in the European Parliamentary Research Service, where he works for the Panel for the Future of Science and Technology (STOA). In this capacity, he “helps MEPs to navigate the hype and work effectively” in technology areas such as blockchain, 3D bioprinting and of course artificial intelligence. His publications have been referenced in the Economist, The Guardian, Al-Jazeera and Wired, among others. He is an observer of the High-Level Expert Group for Artificial Intelligence at the European Commission and coordinates the EPRS writing circle on disruptive technologies. He received his BSc in Artificial Intelligence and PhD in the Management of Science, Technology and Innovation, both from the University of Manchester.
What’s your favorite written piece on AI? I’ll suggest two books that look at AI from my discipline of choice - sociology of technology: Harry Collins (2018). Artifictional intelligence: Against humanity's surrender to computers.. Hannah Fry (2019) Hello world: How to be human in the age of the machine.
How do you define AI in a few sentences? I’d say it’s machines that can respond autonomously to their environment in a way that we consider intelligent. One of the problems with the field is this loose and subjective definition which I think has become an obstacle to productive and meaningful debate.
Are you optimistic or pessimistic about the effects of AI on society? Why? I’m a bit of tech-pessimist in general. For AI, I find it hard to imagine that AI will contribute to the reversal of equating structural inequalities. I think if anything it is more likely to exacerbate them. I think AI (and tech more generally) is seen too much as an end in itself, while the benefits it has delivered so far are much more frivolous than the promises. I think seeing AI as a means to deliver real social value rather than as an end in itself could help improve matters.
What’s the most pressing policy we need to change or develop surrounding AI? I think we need to address the market ecosystem, which tends too easily towards domination. I’m worried about how communicating with others and participating in public debates now seems to require joining private platforms (i.e. facebook and twitter). On a related note, im worried that AI will close down people’s margins of manoeuvre as more aspects of our lives are measured and used as data.
What is the most difficult part of working at the intersection of technology and policy? Probably the speed of technology development, and the hype that can surround some technologies.
What’s one thing people might not know about you? Ah but if I tell then people would know it!
David Bowen is the son of Jamaican immigrants who came to Milwaukee to pursue a better life for their family. Born and raised on Milwaukee’s North Side, David was a 2005 honors graduate of Bradley Tech High School. As a teen and young adult, David completed Urban Underground’s youth leadership program. He was selected as a Legacy Foundation Youth Activism Fellow and is a two-time graduate of the Americorps program, Public Allies. David continued to volunteer with Urban Underground while pursuing his undergraduate degree in Educational Policy and Community Studies at the University of Wisconsin-Milwaukee. Firmly rooted in the community, David became Program Director at Urban Underground. In that capacity, he oversaw creation and implementation of youth programs, services, and professional development training for adults interested in youth civic engagement and leadership development. A nationally recognized trainer for intergenerational community improvement strategies, David served on the Medical College of Wisconsin’s Violence Prevention Initiative Steering Committee and is currently a member of the City of Milwaukee’s Homicide Review Commission. He is also a National Americorps Service Alum. In April 2012 he was elected to the Milwaukee County Board as Supervisor for District 10, becoming the youngest member of the Board and one of the youngest black elected officials in Milwaukee's history. He currently serves on three County Board standing committees: Health and Human Needs, Transportation and Public Works, and as Vice Chair of Economic and Community Development.
State representative Brian Cina is a Progressive State Representative in the Vermont State Legislature. Brian led the effort in Vermont that made it the first state in the nation to form a taskforce examining the role of AI. This taskforce has produced several recommendations, including establishing a permanent commission on AI to support its development and to propose policy initiatives for responsible development. The 14-member taskforce has met regularly since forming in fall 2018 to investigate the field of AI and make recommendations regarding the new technology. In addition to his elected role, Brian has substantial experience in community work, having worked with Americorps and in other social work advocacy roles. Brian received an A.B. in Music from Dartmouth College and an M.A. in Social Work from the University of Vermont. In addition to his role as an elected official, he runs a private practice in clinical work in Burlington, Vermont. He also co-founded ISGOOD (Isham Street Gardening and Other Optimistic Doings), a neighborhood organization that has reduced crime through gardening and other community service activities since 2005. Cina has served as a School Board member from 2014-2017. He led the search for a new superintendent in 2015 and is currently the chair of the Finance Committee. Cina is also a musician and performance artist.
Are you optimistic or pessimistic about the effects of AI on society? Why? I am both optimistic and pessimistic, because AI can be a tool that both solves some of our greatest problems, as it becomes our greatest problem.
What’s the most pressing policy we need to change or develop surrounding AI? Setting boundaries around the ethical use and development of AI.
What is the most difficult part of working at the intersection of technology and policy? Technology evolves faster than policy. We cannot possibly keep up!
What do you hope to achieve by participating in CEPI? I would like to contribute to international policy regarding artificial intelligence because the greatest impact will happen through the policies that we make that go beyond borders. What’s a startup that you think is really cool right now? My baby Gilfeather turnip plants.
Tulsee Doshi is a product lead for Google’s efforts in ML Fairness and Responsible AI, driving a deeper understanding of how to build user experiences that are diverse, inclusive, and ethical. Her goal is to drive a human-centered approach to the development of machine learning-based technology and experiences, to build systems that can truly work for everyone. Tulsee partners with product teams across the company to identify concerns and drive improvements related to fairness, transparency, and broader responsibility. She also partners with research scientists and engineers to determine and implement a research agenda related to Responsible AI.
What’s your favorite written piece on AI? While not an opinion piece, I love the PAIR Guidebook, published by Google, as a written guide for designers to develop AI products that preserve their magic while still working well for users.
How do you define AI in a few sentences? AI, short for Artificial Intelligence, is the simulation of human intelligence, built and manifested by machines. The most common variant of AI is machine learning -- the art of learning from data to develop complex patterns and predictions.
How can we envision or describe data in a sentence or two? Data can be anything, a single point that describes a moment in our stories and our histories. Data holds extreme power, and yet, by itself, is not useful. The meaning we ascribe to data, in how we develop our models, how we visualize and tell stories this data, and how we aggregate and combine it is critical, and makes data the backbone of all our products and technological ventures.
What’s your favorite AI lecture/podcast/video? Joy Buolamwini: AI, Aint I a Woman?
What is the most difficult part of working at the intersection of technology and policy? A challenge I often think about is that there are only a few of us who work at the intersection of technology and policy, when really, these should be two fields that are taught hand-in-hand, and that work hand-in-hand. Making policy decisions can’t be independent of understanding the technology. Otherwise, we make policies that are impossible to enact, and enact changes that need policy oversight.
A relative newcomer to politics, Johannes previously worked in the financial sector in Hong Kong and London. He holds master’s degrees in Finance and International Public Management from HEC Paris and Sciences Po. He is interested in finding ways to clarify and structure ownership rights to algorithmic applications. That includes recognizing the value of the data that is used to train them, and ensuring that owners of data participate in the value creation of the application or platform.
Are you optimistic or pessimistic about the effects of AI on society? Why? I don’t know yet. AI coming of age in an era of open geopolitical conflict and authoritarian governments may do more harm than benefit - but I would not dare to predict the future.
What’s the most pressing policy we need to change or develop surrounding AI? Governing ownership rights of algorithmic applications and the data that is used to train them
What is the most difficult part of working at the intersection of technology and policy? To keep up with technological and commercial reality.
What’s your favorite quarantine song? Raksit Leila by Mashrou’ Leila
What’s a startup that you think is really cool right now? Volt, the political startup I work for of course :-).
Stefan Krabbes is a parliamentary assistant in the office of MEP Anna Cavazzini, a member of the Committee on International Trade (INTA) and a member of the Greens. Stefan joined the European Parliament in the fall of 2019 after nearly a decade working in local, state, and federal politics in Germany. His educational training focused on political science and sociology.
Stefan bemoans “digitization” as a buzzword and is interested in artificial intelligence and the digital world from a philosophical and policy perspective. In his free time, he is a tech blogger and podcaster on his website, where he covers politics, digital issues, and culture.
How do you define AI in a few sentences? If one says industrialization was the outsourcing of physical works from human beings to machines, digitization is the outsourcing of mental works from human beings to machines. Focusing on the part of digitization artificial intelligence is more the creative and smart solving of problems (at least finding possible solutions) by “machines”. But for sure, there is a difference between machine learning and ai. Via machine learning you can program a robot to let it climb the stairs and it improves the climbing step by step. Via ai you can ask the robot to bring you the glass of milk from the kitchen and it completely knows what to do. That’s my definition, even if it's more a description.
How can we envision or describe data in a sentence or two? Data is fixing points of our lives. Based on a German movie about Alexander von Humboldt, I’d say that digitization is the new measuring of our world by using these fixing points. But there’s a saying data is the new oil. This saying may work from the perspective of earning money, but there is a difference: data’s unlimited.
What is the most difficult part of working at the intersection of technology and policy? The basic work and basic understanding. Digitization is used as a buzzword, currently - especially in political circles, when one tries to be hip and tech-affin. It detracts from the seriousness regarding this issue.
What’s a startup that you think is really cool right now? Holochain.
What’s your favorite movie? Into the wild.
Leif-Nissen Lundbaek received academic training as a mathematician, and his work focuses mainly on algorithms and applications for privacy-preserving artificial intelligence.
In 2017, he developed the eXpandable AI Network (XAIN) as a cyber-security protocol that combines AI with privacy paradigms. Since then, his company has won multiple awards, such as the Porsche’s first-ever Innovation Contest, and worked successfully with many blue-chip companies.
He received an M.Sc. in Software Engineering at University of Oxford with distinction as well as an M.Sc. in Mathematics at Heidelberg University.
How do you define AI in a few sentences? AI or machine learning is a programmatic way of automatically looping via one or more statistical layers to come up with decisions or forecasts in more or less complex probabilistic scenarios. There may be data as an input for training e.g. for model based AIs but not necessarily if we think of policy driven reinforcement learning.
How can we envision or describe data in a sentence or two? Data can be numeric, characteristic or symbolic values that describe facts or statistics. It is used to describe or define events as an input for human or machine understanding, yet, neither machines nor humans need (past) data as input necessarily.
What’s the most pressing policy we need to change or develop surrounding AI? In my view it is the question about data sovereignty and privacy. There is a lot of industry pressure that wants to gain massive access to user data for free. However, the data belongs fundamentally to the users and not to any company. It is also simply not true that companies require access to this data to deliver great services. We have technical possibilities to deliver the same services and convenience whilst guaranteeing the highest possible data privacy protection. And if a company really wants to have the data of users in plain text they should pay for it. Delivering convenience or a specific service is just not enough.
What is the most difficult part of working at the intersection of technology and policy? The complexity of merging law and technology is always challenging due to the pace of technical development and the slowness (not in bad meaning) of policy.
What’s your favorite book? Superintelligence: Paths, Dangers, Strategies by Nick Bostrom.
Melanie Meyer has worked for a decade in the office of MdB Peter Beyer, who coordinates transatlantic cooperation for the German federal government. In her current role as senior policy advisor and chief of staff, Melanie’s portfolio focuses on foreign and security politics, economic aspects of politics (transatlantic, Western Balkans, Europe), as well as digitization and 5G. In 2019, assisted Mr. Beyer in preparing for a major digitization and AI conference in Silicon Valley. She has both a bachelor and master’s degree in art history from Heinrich-Heine-University in Dusseldorf.
What’s your favorite written piece on AI? Salomons’s Code: Humanity in a World of Thinking Machines, by Prof. Dr. Olaf Groth.
Are you optimistic or pessimistic about the effects of AI on society? Why? The use of AI has a great potential. It is an essential means to shape the way we want to live in the future. It promises the optimization of processes, fast decision-making but could also involve a loss of control and an ethical debate of the technology in order to generate the trust of the users or customers. The more powerful an AI-System, the greater the responsibility of the user. There can be disagreement over when and where exactly AI begins and where it’s natural or technological (i.e. scientific) limits are. Ethical standards are very important for an optimistic future of AI, so that the user can engage in innovation and that one has not to fear disadvantages, non-transparency or data misuse. There are chances and risks, which are not balanced, but in my opinion the chances are greater. Important to me from the outset is the bottom line that AI has to always serve human kind.
What’s the most pressing policy we need to change or develop surrounding AI? Digital change and AI have to go side by side. AI needs visions and rules. Basis understanding: AI has to serve human kind. Not more. Not less.
What is the most difficult part of working at the intersection of technology and policy? To put it bluntly, you could analyze it as follows: Think big and act quickly is not the strength of politics, but the spirit of AI.
What’s your go-to quarantine drink? Coffee - black, like every morning.
Luca Ravera is an administrator in the European Parliament, where he has spent the last five years in the parliamentary Committee of Transport and Tourism. In the role, he has experienced firsthand the beneficial impacts of AI. He is part of an expert working-group that focuses on future legislative actions relating to AI. His expertise includes intelligent transport systems, autonomous cars, traffic management, drone taxis, and smart cities. Luca holds law degrees from the University of Torino and an LLM in European law from the College of Europe.
On whether or not he is optimistic about AI, Luca prefers to view AI as a tool. “There is no implicit good or bad to AI,” he says. The “good” or “bad” of AI will rather be based on data we insert, how well we train the AI, and AI testing. On the policy side, Luca is particularly interested in civil liability and insurance. He believes that we need to regulate data governance, issues of privacy, and civil liability related to product defects, as well as possibly thinking about schemes of mandatory insurance.
Luca finds that one of the hardest parts of working at the intersection of technology and policy, particularly regarding AI, is that it is akin to working in “unknown territory.” He finds that it is “difficult to have a legal framework which regulates in advance all the applications of AI and stays in line with the times and rapid changes.”
How can we envision or describe data in a sentence or two? Data is all around us. The Internet of Things (IoT) and sensors have the ability to harness large volumes of data, while artificial intelligence (AI) can learn patterns in the data to automate tasks for a variety of business benefits. Any inaccuracies in the data will be reflected in the results, exactly like humans getting wrong information and failing a test.
What’s your favorite written piece on AI? The people Vs Tech: How the Internet is Killing Democracy (And How We Can Save It) by Jamie Bartlett and Homo Deus by Yuval Harari.
What’s the most pressing policy we need to change or develop surrounding AI? I believe we need to regulate data governance, issues of privacy, civil liability related to product defect and possible damages to victims. Possibly also introducing a scheme of mandatory insurance.
What is the most difficult part of working at the intersection of technology and policy? It is the fact of working in unknown territory. It is very difficult to predict all the implications and the consequences AI will bring to our society. It is even more difficult to have a legal framework which regulates in advance all the applications of AI and stays in line with the times and the rapid changes.
What’s a startup that you think is really cool right now? Einride, providing transport services in autonomous electric vehicles.
Jana Schneider works as a policy advisor to MEP Dr. Andreas Schwab, the EPP Coordinator in the Committee on Internal Market and Consumer Protection (IMCO). In this capacity, Jana helps establish the position of the EPP group on all legislative files in the IMCO Committee and assists in drawing up corresponding legislative amendments. Currently, she is helping develop a balanced regulatory environment regarding questions of liability or fairness of decision-making of AI applications. An integral part of her role is harmonizing EU policy concerning AI. She is a lawyer by training and has two master’s degrees in human rights law from Panthéon-Sorbonne and Panthéon-Assas in Paris.
What’s your favorite written piece on AI? On digital development in general one of my favorite books is The Circle by Dave Eggers. To me, it is the 1984 by George Orwell for the digital age.
How can we envision or describe data in a sentence or two? Data is the raw material of the 21st century.
What’s the most pressing policy we need to change or develop surrounding AI? Technical development is very fast-moving and it seems like the policy-maker is often running behind the developments rather than setting a framework in advance to foster innovation while making sure regulation is put in place where necessary.
What is the most difficult part of working at the intersection of technology and policy? Policy making mostly focuses on the “big picture”. When discussing technology, it is often important to understand technical details. To bring the details and the “bigger picture” together is a challenge for policy-making.
What’s your go-to quarantine drink? Probably coffee. As I am working from home at the moment, I have been enjoying using my own coffee machine a lot.
Steinicke is a foreign and geopolitical analyst. Growing up in West Berlin, he was introduced to international politics early on as a child when the Wall came down. Today, he is the Chief of Staff and Foreign Policy Advisor in the office of MdB Christoph Matschie, where he focuses on digitization and foreign policy, including Germany’s 5G debate. He graduated Magna cum Laude from the University of the Armed Forces in Munich with a PhD on Germany’s geo-economic and environmental engagement in the Arctic.
What is the most difficult part of working at the intersection of technology and policy? The equal lack of understanding of both sides. Many policymakers, who are not dealing with technology issues on a day to days basis basically lack digital literacy. Likewise, many techies are a) not aware of the many societal implications of their developments and b) not aware of the political processes a democracy is based upon.
What’s a startup that you think is really cool right now? Not really a startup in the classical sense. The Danish Ministry of Foreign Affairs came up with the idea of TechPlomacy, realising that diplomacy needs to getter a better grasp of how technology changes geopolitics. Hence they set up a team with outlets in Silicon Valley, Copenhagen, and Beijing. It´s the attempt to bring a startup and technology mindset to the foreign affairs and diplomacy community
What’s one thing people might not know about you? I was filmed by a CNN crew in 1990 as a six-year-old in front of the German Bundestag wearing a Soviet officer´s cap (straight after the Fall of the Berlin Wall, Soviet soldiers started selling their equipment on the streets of Berlin).
What’s the most pressing policy we need to change or develop surrounding AI? If you believe what AI thinkers like Kai Fu Lee and Yuval Harari are saying, it is to significantly invest in people´s ability to develop empathy as well as to invest in social work jobs as this is a massive growth job market.
What’s your go-to quarantine drink? Coffee.
Louisa Well is a policy advisor to MdB Dr. Anna Christmann, who currently is the Spokesperson on Innovation and Technology Policy for the Greens. Louisa manages work relating to the Parliamentary Finding Commission on AI and the Committee on Digital Affairs, writing parliamentary initiatives and organizing events on AI and digitization. She won the David Edge Prize for her master’s thesis on automated unemployment at the University of Edinburgh.
How do you define AI in a few sentences? AI, in a machine learning sense, can do so many things by finding patterns in large data sets that humans wouldn’t be able to see. In every sector, machine learning can play a role and change how we are solving problems: be it to find new vaccines, re-organize transportation or combat climate change. What fascinates me most are the societal changes this new form of decision making will bring.
Are you optimistic or pessimistic about the effects of AI on society? Why? It can be used to both ends and I don’t think fundamentally rejecting or embracing helps us making the best of AI; I prefer thoroughly understanding the system, making use of the good and exposing the bad. For this, we need educated societies that have debates about pending value judgements. Rather than yet another panel talk on the trolley problem of autonomous driving, we need to answer questions of how we can we foster innovation, improve living standards and reduce inequality.
What’s the most pressing policy we need to change or develop surrounding AI? Make AI more diverse and create spaces to develop ideas on how to tackle climate change and reduce social inequality.
What’s your favorite book? I recently read Humankind: A Hopeful History by Rutger Bregman, which I quite enjoyed because, like all the books that leave a lasting impression with me, it gives plenty opportunities to discuss new thoughts with people around me.
What’s your favorite quarantine song? Line of Fire – Junip.