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EXECUTIVE SUMMARY
Context and why this is important
The intersection of machine learning and genetic engineering is speeding up development of new technologies and new applications creating transformational opportunities as well as difficult ethical challenges for society as a whole. The combination has opened doors to advances in medicine which change the way we understand health. But its potential extends beyond health in development of new materials and genetic engineering across biological organisms and in adapting biological processes. Parallel advances in robotics and automation are another force for acceleration. And, we don’t yet know what further dimension quantum computing could bring.
As the physical becomes digital, the opportunities for individuals will be life changing. Such technologies could have impact on people’s identities, personal morality and ethics. For societies, new kinds of inequalities could result, bringing fresh challenges for democratic processes. National economies will change and dual use means there are new threats to security. Autocratic states will follow different paths. And yet, questions of governance lag far behind. How social values and norms inform the ways technology develops is far from clear.
People
This conference brought together a mix of expertise including geneticists and biologists, biotechnologists, microbiologists; thinkers on philosophy, religion, law and machine learning, investors and a range of company founders.
Analysis
We felt like explorers of a whole new continent of opportunity and risk.
Presentations on genomic prediction and the significance of current applications in IVF and embryo selection quickly captured attention. Other features of the intersection of machine learning and genetic engineering, such as the understanding of human and computer interaction; uses in plants and agriculture; uses in warfare and the implications for security, were raised but issues of healthcare and the implications of embryo selection dominated because the dilemmas are already playing out and are urgent.
Society has yet to catch up. Establishing values, norms and regulation to facilitate the continued advance of the technology requires a deeper understanding of potential applications of machine learning and genetic engineering to map 2nd, 3rd and 4th order, as yet unknown, effects.
The interests of individuals wishing to select better outcomes for themselves and their offspring may well clash with the interests, longer-term, of populations as a whole. The question of the environmental impact on genetic expression would not go away. If we optimise ourselves for the environment we have now, and it then changes, what then? Are all bets off for genetic engineering if the environment changes? Do we have to learn to shape the environment as well as ourselves – which man has always sought to do?
Geography; research, applications and governance follow different tracks in different in parts of the world. What is acceptable and in fact happening already in some countries is not acceptable in others. What happens next?
Responses – not consensus, but ideas emerging
We need better maps of technological pathways and accompanying explanatory narratives. Calls were made for models, visualisations, scenarios and mapping with explorations for example of potential 2nd/3rd/4th order effects and unintended consequences. Alongside modelling, we need exploratory narratives to help develop our collective understanding of what is happening, what could happen and what the various publics in different parts of the world want to happen.
Don’t give up on multilateralism. Regulation at a multilateral, multinational level should be explored. Despite the doubt and concern over the effectiveness of multinational institutions – opportunities remain for collective frameworks for governance and regulation that reflect widely shared values. There are opportunities for the G20, WHO etc.
New approaches to data that allow use of anonymised data and support innovation, which could unlock the potential of this new field of technology and science should be a focus for research.
Focus innovation on where publics want to see change – for example, in oncology and cancer treatment.
Realise early that this is a contemporary security issue as well as a health issue.
FULL REPORT
Context
The aim to set out a checklist for society of the opportunities and risks unfolding with the convergence of machine learning and bio-engineering was ambitious.
The development of gene editing techniques and the drop in the costs to do it have been incredibly rapid. Over the last 20 years, research has accelerated to the point of therapeutic applications in humans (as well as for crops, agriculture, bacteria and antibiotics). The knowledge has moved from academia to commercial companies and the implications are enormous. IVF has been around for many years but additional innovations, for example in embryo selection (to help reduce genetic diseases) and then to precision gene editing, will, over time, modify the genetic make-up of population groups. The stakes are high, the developments in biology will inevitably run into the context of politics and regulation and ethics but the wider public debate that must inform its governance has not yet happened. The security risks of deliberately destructive or hostile uses of this technology have yet to be understood. Technological capabilities are ahead of public debate. Some suggest the inevitability about converging technology means we must embrace these innovations in order to compete and survive. For others, the rate of change means we must step back and be prepared to call a halt and change direction. But how can we do this in a multi-polar world without an overarching global governance or order, a world where the race to invest and expectations for returns, are already high?
Fast, cheap, globally distributed, with capacity for bottom-up development – the features of this technology are also the features that contribute to huge uncertainties over the direction of development. The amazing opportunities for the elimination of genetic disease and human transformation foreseen by some, is matched only by the uncertainty and dystopia feared by others: both can be felt at one and the same time, and by the same person!
People
A discussion such as this requires a diversity of expertise, views and approaches. The conference brought together very senior academic expertise in genetics, cybernetics, machine intelligence and quantum technologies and newer interests in synthetic biology, together with experienced figures in bioethics, law, security, regulation, data-ethics and investors. Expertise in politics, policy-making, theology, technology, business development and commercial bioscience was also central to the discussion.
Analysis
The impact of genomic prediction. The conference began with an account of very recent advances in computational genomics and genomic prediction using population data to identify outliers that indicate risks for particular diseases. These advances are delivering new information about individual health risks that are informing current medical practice. For example, a risk score for breast cancer provides new information that (it was suggested) is unethical for medical professionals to ignore. The further incorporation of polygenetic risks, where characteristics are controlled by more than one gene, were also already being calculated in medical settings.
The current limitation to disease identification was said to be the availability of data. With increased availability of data (including improvements in capacity to verify across different population groups), and improved facility to incorporate other non-genetic information in predictive processes, it is possible that advances in predictive-based medicine may change our understanding of human health and deliver new and important benefits for public health.
The increase in accuracy of such prediction is accelerating the capacity for disease identification and importantly for other non-health related human characteristics such as height and eye colour. Perhaps most contentious was the claim that this technique could include selections for non-medical traits such as intelligence and cognitive abilities.
The machine learning part. Convergence brings new orders of complexity. The capabilities of machine learning in performing specific tasks such as image recognition are so much more powerful than human capabilities. But with machine learning the computer determines its own rules and processes for achieving the task set. The intelligence at work is different from human intelligence. The inductive biases of the computer, as a consequence of massive accelerated improvement of the processes it follows, diverges from human learning processes. The computer’s mode of operation – their intelligence – becomes harder to fathom, even alien. Machine learning can become a black box with risks from the loss of human control. If a computer responds in unpredictable ways (i.e. it reads signals not detectable to humans or not anticipated by the human algorithm designers), the outcome could be dramatically wrong or at least wrong in human terms but correct according to algorithmic- based learned logic. At this point, the interests of humans and computers could diverge – or wholly new insights might emerge.
[New ways of communicating with computers and using machine learning that don’t rely on huge data sets or raw data (which may also contain biases) but derived from hybrid specifications, were said to be in development.]
Immediate responses to the outline of genomic prediction and machine learning methods raised an eclectic mix of concerns:
- There is no infrastructure of doctors/genetic counsellors to support these developments – what happens when people want and need support to make decisions and interpret outcomes?
- It is possible that these methods could lead to multi-tier health services with different levels of access responding to wealth, knowledge and awareness of the potential benefits.
- It will be the better off who get their genomes sequenced and take advantage.
- What’s the point of predicting cancers we don’t know how to treat? How does this relate to preventative health?
- Global population increase will take place mainly in Africa – the predictive models don’t yet work with people of African heritage.
- Should the research and innovation effort be focussed on plants – food is more fundamental?
- Is the future a vision of IVF and selection of preferred characteristics, traits and predispositions for behaviour? What about the risk of mistakes that create second or third order effects or even conflicts that we cannot yet know?
- How are environmental factors accounted for?
- What about the impact of, and interaction with, the microbiome?
- How do commercial companies make judgements about where to draw the line? And, what about the competitive pressure for new entrant IVF companies to offer what rich parents want? Even if a company takes an ethical position to withhold information about non-medical traits, other companies in other more permissive jurisdictions will quickly step in to meet the demand.
- How will these developments be monitored for their effects over time?
- How do we understand correlation and causality? Once correlation is established is that good enough to extend wider treatments?
- How are wider social value judgements (across different cultures, societies and populations) to be taken account of in these processes?
- Will governments eventually be intervening to redistribute genetic power in the same way as they intervene to redistribute wealth today through the tax and welfare system? The mechanism for this would be to offer couples with a genetic inheritance judged to be lacking (and there are multiple questions about this judgement itself) a choice of additional embryos in IVF so as to have a better chance of choosing one with excellent characteristics.
Ethical guidance. Is there a satisfactory ethical framework to manage the change implied by this technological convergence or not? The last 70 years of related research in key technologies and health sciences has provided a substantial network of regulations, guidance, rules, protocols and declarations. Peer review, patenting and bioethics commissions add to what was described as an active and evolving ecosystem. But is it enough and does it address the right things in relation to machine learning which is different because, although it is human informed, it is not human end-to- end, and the speed of operation makes machine learning qualitatively different from what has gone before?
Data. The core processes rely on the availability of data. The question of how the required data can be acquired more quickly hovered. Could there be better international sharing of data by major data producers such as China and India? Genetic prediction is related to ethnicity and there is a need for complex mixes of population data. Fundamental questions about how to approach data, privacy, ownership and balancing of personal interest with collective benefits played out – yet again. There are big choices to be made about how citizens use/sell or benefit from their data and new thinking about how to respect privacy by anonymising large datasets. Do we need new institutions to govern the generation and provision of data needed for research and innovation?
Can we be more precise about the distinction between the ethics of research and the ethics of treatment? A public debate about the use and need of data is essential. UK research projects such as UK Biobank, The 100,000 Genomes Project, and Generation Scotland are public engagement initiatives in their own right. In the US, as well as public research projects, there are commercial models in which people either sell their data or buy, at low cost, genetic profiling and give permission for companies to use or sell their data on. A number of projects in the US and China are exploring the opportunities systematically to collect genetic sequencing of new-borns. There are many implications: the centrality of data for example, may change the doctor-patient relationship as the doctor becomes an intermediary for data collection.
Political issues. The technology has converged in ways that bring together academic and commercial interests. Much of talent and expertise in machine learning is concentrated in the private sector. The wider public health debates have yet to be had. The reliance on big data sets and rapid acceleration and complexity of insight creates particular questions about benefits to individuals and benefits to populations. The two are obviously related but their interests are not necessarily the same. The active capability for altering cells, changing and adding genetic code, sits uneasily with processes for assessing and diagnosing disease for which there is no cure. Who decides and has the right to decide where research effort and resources should go? How are longer-term consequences to be monitored and managed in these new areas of convergence, particularly in the light of potential change to germline somatic cells? Are we moving from disease-centric models to a redefining of health and health systems?
These questions sit within a larger context of the volatility of geopolitics. The rate of research and investment is uneven around the world – different values, norms and regulations apply. Investment and patents are accelerating in Asia. Stem cell therapies are approved in some regions and not others. Some countries are operating below the level of global standards. There are new entrants, new players, new funders and new stakeholders. Disintermediation, ‘forum shopping’ and ‘regulatory arbitrage’ is already at work. Do we understand how the cash flows, what the incentives are that shape development and the capacity for high net worth individuals to step in and change the face of genetics research? New entrants bring different values into play. Will the libertarian values that characterised the development of internet companies dominate the commercial emergence of synthetic biology and genetic engineering?
In a multi-polar world in which the rules-based international order is contested both by the deep distrust peoples have of their ruling liberal democracies and by the dramatically increased global power of autocracies, the potential for machine learning-driven genetic engineering could bring enormous benefits for public health worldwide. It could also facilitate malevolent forces to apply the technology at scale to subdue populations or build a more pliable society – for example, with the use of facial recognition or enforced embryo screening.
Individuals & society. These political questions bring us back to fundamental ethical questions about what human genetic enhancement might bring and to what end – what does it mean to be human and to flourish? Is it right that we should attempt to answer these questions now and foreclose the opportunity for future generations to come up with different answers in future? Society is a networked system with people playing valuable roles in society for different reasons – but who would willingly accept that their child be the useful weaker link? Will these questions be discussed more widely outside the academic institutions and commercial companies? What kind of infrastructure for public engagement exists outside of institutions? Convergence is creating interdisciplinary approaches that require a shared vocabulary, particularly around discussion of prediction. This vocabulary has yet to emerge in policy or in politics.
Inequality. The risks for applications of the technology to drive new and entrenched inequalities were uppermost for many. It is not just a concern that the rich will adapt and drive their own advantages to preserve and extend their life or enhance their off-spring whilst others who may benefit from techniques to exclude risks of disease will not have access. It is also that wholly new dimensions of inequality could be introduced in the concept of the gene-rich and gene-poor. If immediate self-interest of the wealthy can trump the good of collective populations or lead to a situation whereby the least well-off carry the genetic diversity needed for the long-term future of the human race but lose out in the short-term, the potential inequalities are staggering. The prospect of genetic echo-chambers isolating population segments is one to be managed. Will the current reliance on data of western gene pools mean that the technological pathways of precision medicine reinforce existing inequalities? The idea of ‘bounded inequality’ was put forward as a means of limiting excess.
Democracy. These potential applications are bearing down on us fast. The debate on human enhancement throws up many questions about what is meant by enhancement, whether attempts to enhance are optimising for the world we see now, which may be about to change. Would peer pressure drive attempts to enhance children? Could autocratic states impose requirements for enhancement? How will democratic processes take charge and control the expression of the technology? The risk that democratic states are losing mechanisms for the oversight of innovation was a concern.
Regulation. Governance will have to transcend national boundaries. The convergence of technologies does not respect national boundaries. There is much uncertainty over how best international mechanisms can be developed. Who defines regulation at the state or global level? Regulatory arbitrage is already happening. Certain treatments are offered (stem cell treatments regulated in the Bahamas) but banned in the US. Some treatments are licensed in Japan that are not licensed elsewhere. Patients (who can afford to) will self-select where they go.
There is also concern that regulation could hinder learning and development and hold back innovation. Attitudes can change: IVF, which caused huge concern when it was introduced, is now widely accepted.
Is the public health framework of risk/benefit analysis the right approach to take? And, is it acceptable to develop a regulatory framework for decisions that may affect millions to be made by a small group of like-minded peers? How can transparent decision-making be put in place with a wide-reaching framework to protect health, security and the environment?
[There was doubt about how well democratic nation-states are positioned to capture the value of innovation and adapt to general purpose technology with the potential to disrupt political, economic and cultural systems. A multi-lateral layer is needed.]
It was difficult to see western states as both permissive and responsive in the way that China – described as having a more febrile innovation culture – has been. The shift of knowledge and technology from an academic voyage of discovery to commercial exploitation in ways responding to markets for healthcare does not respect national boundaries.
[Oncology, tackling malaria and responses to longevity and aging were seen as likely drivers. The emergence of the fit elderly challenges decision-making based on chronological age and could change age-development economics.]
The discussion of regulation tended towards applications, products and uses where there is already some reliance on the use of patents. There was much less discussion about policy and how to set the terms for research and development. Regulation, it was suggested, can build certainty and trust and so support innovation. Opportunities for clubs and soft law mechanisms to support responsible and ethical innovation (for example iGem) were seen as very promising.
Security and the precautionary approach. The convergence of machine learning and genetic engineering is not just a debate about the future of public health and embryo selection. The technology brings new possibilities to create new pathogens or re-create extinct pathogens and to modify aspects of human biology such as the immune system. A security approach rests on managing uncertainty and ambiguity. Risk benefit calculations were not (some suggested) the way to evaluate biological research with high misuse potential. Instead, application of the precautionary principle that emphasises ‘first do no harm’ would shift the emphasis to research funders, scientists and publishers to prove the absence of danger. However, all technology can be weaponised – the challenge is to find ways to manage the uncertainty.
Leadership. The discussion of regulation and a precautionary approach quickly led to calls for better leadership. How will the international community address these issues? Is there scope for the G20 to develop regulatory approaches? Can university systems provide the preparation work for regulatory deals?
Lower costs may well allow new entrants (low resource countries, companies and national militaries) that have not as yet been players. It may be that states with less to lose may be willing to take more risks.
Are our political leaders sufficiently familiar with these issues? Could we see a more profound repeat of the political failure to understand how internet based commercial platforms work – an international collective failure that has allowed the emergence and overwhelming dominance of a few companies to determine the future?
The new knowledge created by convergence of technologies and academic disciplines was said to herald a new age of enlightenment in part driven by a better understanding of epigenetics. But there are huge uncertainties and potential disruptions to the way this new knowledge emerges.
Public debate. The lack of public awareness of the technological capabilities and their implications was raised again and again. Is the point of connection advances in medicine that address, for example, cancer or tackle malaria? Is it about advances in IVF and an ability to select embryos with reduced risk of disease? Is it about rethinking public health and sharing new understanding of epigenetics which have direct implications for the lifestyle choices we make or what we do with new genetic information?
For the UK, the strategic review of the NHS and the discussion of improving health care delivery and saving on costs provides a practical point of connection? What about setting the terms that permit fundamental research, sharing the understanding of security risks, malevolent applications and the implications for new forms of inequality or social control?
The priority for some was the development of values, norms and regulations to help frame the further development of new capabilities. But there was real uncertainty over whether this was a call for public relations to prepare populations to accept these changes or a call for genuine engagement with diverse and unpredictable publics.
The trajectory of development will be different in different parts of the world. The UK has some advantages (for example in research and data) that it shouldn’t lose. Regulations, rules and democratic principles must be applied as best they can. These practices can build to influence and inform the global governance institutions. Norms can be developed now – bottom up. There is creative thinking to be done on how multilateral institutions can go forward in partnership with the private sector.
Areas raised but not discussed included opportunities for the technology to be used to tackle ocean pollution and to modify the ways we consume natural resources, energy and food. The implications for services, insurance, education and pensions were not discussed. The potential to create applications using DNA to help fight crime or identify criminals wasn’t included. Stem cell technology and biotechnology/AI in the area of personalised medicine was mentioned only in passing. The potential to reconfigure global power relationships and the creation of new winners and losers was not discussed. The promise of automated laboratories that might change the way research is done and potentially open up to new and more researchers (including citizens) or the way AI is now linked to modern biology were touched on but merit further exploration.
Responses – not consensus but ideas emerging
Don’t give up on multilateralism. It remains an important means of developing shared rules, regulations and norms. Forums that encourage globalisation of regulatory frameworks must be explored. What opportunities are offered by the G20 for example to deal with rogue states/actors? Are there opportunities to collaborate with China over regulation and rule setting at the multilateral level?
Develop the security framework and create alert mechanisms to identify dual uses or transfers into security risks.
Support linkage across national boundaries. Using the existing ecosystem of regulation (academic and industry tools) that have emerged over the last 70 years – what mechanisms are available to support cross national applications? Develop the opportunities to learn from existing tools translating the learning across academia, policy-making and governments.
Data & Ethics. To support the work of institutes such as the Open Data Institute and the Centre for Data Ethics and Innovation to accelerate new thinking about data, ethics, research needs, application needs, the value of data to citizens and society and the potential to unlock data use for innovation.
Build a better map. Explore opportunities for modelling and visualisations that can be influential analogies helping all levels of understanding, i.e. for publics, policy, business and research uses.
- for example, building models of predicted outputs (in similar ways to spread of HIV);
- open source modelling that private companies might build on;
- Exercise and learn lessons from case studies – responses to epidemics;
- Model potential benefits and harm prevention (unintended consequences);
- Model the development of synthetic biology (the investment and drivers of research and innovation);
- Develop new vocabulary, guardrails, rules and soft-laws to shape and influence global norms;
- Explore collaborative competitions that engender responsible and ethical approaches in their terms and conditions;
- Consider creative approaches to modelling such as the commissioning (competition) of speculative fictions/essays that open up the discourse and shape the emerging narrative.
This Note reflects the Director’s personal impressions of the conference. No participant is in any way committed to its content or expression.
AUSTRALIA/UK
Sir Michael Hintze AM GCSG
Group Executive Chairman and Senior Investment Officer, CQS.
AUSTRIA
Ms Helene Steiner
Co‑founder and Director, Open Cell, London (2018‑); co‑founder and CCO, Cell‑Free Technology Ltd, Ireland (2017‑); Visiting Lecturer, Royal College of Art (2016‑); post‑doctoral researcher, Microsoft (2016‑17); Visiting Researcher, Massachusetts Institute of Technology (2014).
CANADA
Dr Bruce Mazer MD
Executive Director, Research Institute and Professor, Department of Pediatrics, Faculty of Medicine, McGill University Health Centre.
Dr Eric Meslin FCAHS
President and CEO, Council of Canadian Academies, Ottawa (2016‑). Formerly: Indiana University: Founding Director, IU Center for Bioethics, Associate Dean for Bioethics School of Medicine, Professor of Philosophy, Medical & Molecular Genetics, Bioethics & Law (2001‑16); Executive Director, U.S. National Bioethics Advisory Commission, Washington, DC (1998‑2001); Bioethics Research Director, Ethical, Legal and Social Implications Program, National Human Genome Research Institute, Bethesda, Maryland (1996‑98). Fellow, Canadian Academy of Health Sciences (2015‑).
Dr Ashley Moyse
McDonald Postdoctoral Fellow in Christian Ethics and Public Life, Faculty of Theology and Religion, University of Oxford; Associate Fellow, Center for Bioethics and Human Dignity, Trinity International University, USA; member, Centre for Research in Religion and Social Policy, and honorary research associate, Trinity College, University of Divinity, Australia.
Professor Andrew Torrance
Earl B. Shurtz Research Professor, School of Law, Kansas University; Visiting Scholar, MIT Sloan School of Management; Research Fellow, Gruter Institute; Senior Fellow, Centre for International Governance Innovation; founder, annual Biolaw Conference. Formerly: practiced biotechnology patent law, Fish & Richardson PC; in‑house patent counsel, Inverness Medical Innovations; Eliot House Resident Tutor in Biology and Law, Harvard University (1993‑2000).
Dr Alan Bernstein O.C., OOnt., PhD, FRSC
President and Chief Executive Officer, Canadian Institute for Advanced Research (CIFAR), Toronto (2012‑). Formerly: Executive Director, Global HIV Vaccine Enterprise, New York; inaugural President, Canadian Institutes of Health Research; Director of Research, Samuel Lunenfeld Research Institute (1994‑2000); co‑chair, Scientific Advisory Committee, Stand Up 2 Cancer Canada.
FRANCE
Mr Victor Dillard MEng MPhil
Chief Executive Officer and Founder, Desktop Genetics (2012‑); VP of Gene Editing, Celixir plc (2018‑). Formerly: Procter & Gamble, GlaxoSmithKline, Flagship Ventures (now Flagship Pioneering). Chemical Engineer. Forbes' 30 Under 30 for Technology (2017); MIT Technology Review Innovator Under 35 and Entrepreneur of the Year (2017).
NORWAY
Dr Filippa Lentzos
Senior Research Fellow (joint appointment in the Department of Global Health & Social Medicine and the Department of War Studies), King's College London; Associate Senior Researcher, Stockholm International Peace Research Institute; Biological Weapons Convention NGO Coordinator; biosecurity columnist, Bulletin of Atomic Scientists.
POLAND
Mr Maciej Kuziemski
Research Fellow, Program on Science, Technology and Society, Harvard Kennedy School; Advisor, Samurai Labs. Formerly: CEO, Coalition for Polish Innovations; Board Member, Res Publica Foundation.
UK
Mr Gaurav Agarwal
Medical student (BM BCh Bachelor in Medicine and Surgery), Balliol College, University of Oxford (2015‑21); Computational Analyst, Weatherall Institute of Molecular Medicine, University of Oxford (2019‑). Formerly: Summer Intern, Gurdon Institute, University of Cambridge (2018); Summer Intern, Harvard Stem Cell Institute (2017); Project Leader, Oxford iGEM 2016, University of Oxford.
Mr Azeem Azhar
Founder, Exponential View; strategist, product entrepreneur and analyst; Senior Advisor for AI to the CTO, Accenture; editorial board, Harvard Business Review. Formerly: Founder (2010), PeerIndex; Reuters; BBC; editor, The Economist and The Guardian.
Dr Gulzaar Barn
Postdoctoral Research Associate in philosophy, King's College London; BBC/Arts and Humanities Research Council New Generation Thinker. Formerly: Lecturer in Philosophy, University of Birmingham; Postgraduate Research Fellow, Parliamentary Office of Science and Technology.
General Sir Richard Barrons KCB CBE
Managing Partner, Wychwood Partners LLP; Senior Visiting Fellow, LSE IDEAS; Distinguished Fellow, RUSI; Senior Military Adviser CAE(UK) plc. Formerly: British Army (1977‑2016): Commander, Joint Forces Command (2013‑16).
Professor Andrew Briggs
Inaugural Chair in Nanomaterials, Department of Materials, University of Oxford; Principal Advisor for the Power of Information initiative, Templeton World Charity Foundation; co‑author, 'The Penultimate Curiosity: How Science Swims in the Slipstream of Ultimate Questions' (2016, OUP). Formerly: Director, Interdisciplinary Research Collaboration in Quantum Information Processing (2002‑09); EPSRC Professorial Research Fellow.
Professor Dame Kay Davies CBE, DBE, FRS, FMedSci
Professor of Genetics, Department of Physiology, Anatomy and Genetics, University of Oxford (2018‑); co‑Director, Oxford Neuromuscular Centre, Muscular Dystrophy UK (2017‑). Formerly: Dr Lee's Professor of Anatomy, University of Oxford (1998‑2018); Deputy Chairman, The Wellcome Trust (2013‑17); founder, Functional Genomics Unit, Medical Research Council (1999‑2017); co‑founder and co‑Director, Oxford Centre of Gene Function (2000).
Dr James Field
Chief Executive Officer and Founder, LabGenius Ltd, London; Forbes' 30 Under 30 for Science & Healthcare (2018); Fellow, Synthetic Biology Leadership Excellence Accelerator Program. Formerly: BBSRC Innovator of the Year (2017).
Dr Vishal Gulati
Venture capital investor focusing on investments that lie at the convergence of healthcare with internet, data science, AI and engineering; investor/board member, Draper Esprit.
Mr Jonathan Hellewell LVO
Special Adviser to the Prime Minister for faith communities, No10 Downing Street.
Dr Annalisa Jenkins MBBS, FRCP
Non‑executive director of a number of companies; board member, FasterCures, a Center of the Milken Institute, Washington, DC.
Mr Siraj Khaliq
Partner, Atomico.
Professor Ross King
Professor of Machine Intelligence, School of Computer Science, University of Manchester; co‑Founder, PharmaDM.
Dr Pushmeet Kohli
Principal Scientist, Head of Research, AI for Science/Security, DeepMind. Formerly: Director of Research, Cognition group, Microsoft; Technical adviser to Chief Research Officer, Microsoft.
Dr Peter Mills
Assistant Director, Nuffield Council on Bioethics (2011‑); member, World Economic Forum Global Future Council on Biotechnology (2018‑). Formerly: Member, Council of Europe Bioethics Committee (2007‑09 & 2015‑16); Head of Secretariat, Human Genetics Commission, and Head of Genetics and Bioethics, UK Department of Health (2007‑10); reproduction and embryo research policy, Human Fertilisation and Embryology Authority (2000‑07).
Ms Carina Namih
Partner, Episode 1 Ventures, London; Founder, HelixNano.
Mr Charles Roberts
Head of Technology; Juvenescence AI; co‑founder (2015), Freenome, California. Formerly: Visiting Lecturer, Imperial College London (2014‑16); co‑founder and director, Agalimmune, London (2013‑16); co‑founder and director, Premaitha Health, Manchester (2014‑16); co‑founder and director, Centauri Therapeutics Ltd (2013‑16).
Mr Roger Taylor
Chair, Centre for Data Ethics and Innovation; Chair, Ofqual (qualifications regulator); member, advisory panel to Her Majesty's Inspectorate of Probation; author, 'God Bless the NHS' (Faber & Faber, 2014) and 'Transparency and the Open Society' (Policy Press, 2016). Formerly: co‑founder, Dr Foster; correspondent, Financial Times, UK and USA; researcher, Consumers' Association.
Professor Alex van Someren
Managing Partner, Early Stage Funds, Amadeus Capital Partners; Clore Visiting Innovation Professorship, Royal College of Art; member, Science, Industry and Translation Committee, Royal Society (2019); co‑founder, CyLon; Entrepreneur in Residence, Judge Business School, University of Cambridge (2005‑). Formerly: co‑founder and CEO, nCipher (now Thales e‑Security); co‑founder, ANT Ltd.
Mr Matt Warman MP
Member of Parliament (Conservative) for Boston and Skegness (2015‑); Parliamentary Private Secretary to the Secretary of State for Northern Ireland (2018‑). Formerly: member, Science and Technology Select Committee; co‑Chair, All Party Parliamentary Group on Broadband and Digital Communication and The Parliamentary Internet, Communications and Technology Forum; Technology correspondent, Daily Telegraph (1999‑2015).
Professor Kevin Warwick DSc. CEng. FIET FCGI
Emeritus Professor, formerly Deputy Vice‑Chancellor (Research), University of Coventry; Professor of Cybernetics (currently Visiting Professor), University of Reading. Eight Honorary Doctorates from UK Universities and The Future of Health Technology Award from MIT; recipient, Ellison‑Cliffe medal, from the Royal Society of Medicine.
Dr Simon Whitfield
Deputy Director, Government Office for Science, London. Formerly: Department of International Development and HM Treasury. PhD in genetics.
UK/USA
Lady Judge CBE
Chairman, Systematized Nomenclature of Medicine (SNOMED International); Chairman, Astana Financial Services Authority; Chairman, CIFAS (the UK fraud protection agency); Chairman, The Cambridge Code; Deputy Chairman, TEPCO Reform Committee and Chairman of its Task Force on Nuclear Safety. Formerly: Chairman, United Kingdom Atomic Energy Authority; Chairman, UK Pension Protection Fund (2011‑16); Executive Director, Samuel Montagu & Co. Ltd; Director, News International; Commissioner, U.S. Securities and Exchange Commission. A Governor and a Member of the Programme Committee and Business Committee, The Ditchley Foundation.
USA
Mr Kenneth Cukier
Senior Editor, The Economist (2003‑); Associate Fellow, Saïd Business School, University of Oxford; Trustee, Chatham House. Formerly: Wall Street Journal, Hong Kong; International Herald Tribune, Paris; Research Fellow, John F. Kennedy School of Government, Harvard University (2002‑04). Co‑author, 'Big Data: A revolution that transforms how we work, live and think' (2013).
Mr Zavain Dar
Partner, Lux Capital, Menlo Park, CA; lecturer, Stanford University. Formerly: Investor, Innovation Endeavors (drafted firm's theses in Genetics, Synthetic Biology and the Blockchain); computer scientist, Discovery Engine (acquired by Twitter); co‑founder, Fountainhop; researcher, AI Lab, Stanford University.
Dr Kevin Davies
Executive Editor, The CRISPR Journal; Editor‑at‑Large, Genetic Engineering & Biotechnology News (2017‑); Founding Editor, Nature Genetics (1992‑); co‑author, 'DNA: The Story of the Genetic Revolution' (2017; with James D. Watson). Formerly: Guggenheim Foundation Fellow (2017); Editor‑in‑Chief, Cell Press (2000‑01).
Dr Christopher Gibson
Founder and CEO, Recursion Pharmaceuticals, Utah.
Mr Xavier Gonzalez
Rhodes Scholar; MSc Candidate in Mathematical Sciences, Balliol College, University of Oxford. Formerly: Intern, Mesirov Lab, Department of Medicine, UC San Diego.
Mr Daniel Grushkin
Founder and Executive Director, Biodesign Challenge; journalist on the intersection of biotechnology, culture and business for Bloomberg Businessweek, Fast Company, Scientific American and Popular Science. Formerly: Co‑founder (2009) and Executive Director, Genspace; Fellow, Woodrow Wilson International Center for Scholars (research in synthetic biology) (2013‑14); Emerging Leader in Biosecurity, UPMC Center of Health Security (2014).
Professor Stephen Hsu PhD
Senior Vice President for Research and Innovation and Professor of Theoretical Physics, Michigan State University; scientific adviser and member, Cognitive Genomics Lab, BGI (formerly Beijing Genomics Institute). Formerly: Director, Institute for Theoretical Science and Professor of Physics, University of Oregon; Founder and CEO, SafeWeb (acquired by Symantec); founder, Genomic Prediction, Inc.
Professor Michael Imperiale PhD
Arthur F. Thurnau Professor, Department of Microbiology and Immunology, and Associate Vice President for Research, University of Michigan; Founding Editor‑in‑Chief, mSphere.
Mr Nan Li
Managing Director, Obvious Ventures, San Francisco; adjunct lecturer on venture capital, Stanford University. Formerly: Innovation Endeavours; Product, Operations and Finance, Gigwalk; VC, Bain Capital Ventures; Project Manager, Microsoft.
Dr Amy Liao
Co‑Founder (1999), President (2018‑, following Brooks' acquisition of GENEWIZ) and Chief Executive Officer (2017‑), GENEWIZ (global provider of genomics services, including Sanger sequencing, next generation sequencing, gene synthesis, molecular biology and GLP/CLIA regulatory services).
Dr Jamie Metzl
Technology futurist, sci‑fi novelist; syndicated columnist on Asian affairs, genetics and virtual reality; founder and co‑Chair, Partnership for a Secure America; Advisory Board member, Brandeis International Center for Ethics, Justice and Public Life; author: 'Genesis Code', 'The Depths of the Sea' and 'Eternal Sonata'; forthcoming: 'Homo Sapiens 2.0: Genetic Enhancement and the Future of Humanity'; partner and Head of Strategy and Research, Conversion Capital, New York. Formerly: Executive Vice President, Asia Society; White House Fellow; Aspen Institute Crown Fellow.
Niven Narain PhD
Co‑founder, President & CEO, Berg Health, Boston (inventor of Interrogative Biology® platform); pioneer in use of patient‑driven biological modelling and artificial intelligence (AI); author of over 550 issued and pending US and international patents covering the use of AI and biological systems modelling for drug development across multiple disease areas; member, NASA/Gene Lab Steering Committee; EY Entrepreneur of Year finalist (2018).
Ms Hannah Schneider
Rhodes Scholar; DPhil Candidate in Music, University of Oxford.