2019 Ditchley Foundation Conference

[WORK IN PROGRESS]

Welcome to the discussion about the Ditchley Foundation conference on the intersection of machine learning and genetic engineering, 7-9 February
Hackuarium Association Hackuarium is invited to help shape policies and drive a discussion around 3 topics

The intersection of machine learning and genetic engineering: what should be our checklist for society and state as we blast off?

DISCUSSION GROUPS

Working group meetings are held in the Tapestry Room, the Library and the West Wing Drawing Room. (The Tapestry Room is located on the front western side of the House, and the West Wing Drawing Room on the west side, through the colonnade). (What is this, V? the place in England where you will be on Thursday???)

GroupA

The impact on health, personal identity, purpose and the relationship between groups of people Questions such as those from 1-12 in the terms of reference.

GroupB

National economies, work, equality, society and democracy Questions such as those from 13-23 in the terms of reference.

GroupC

Competition and power struggles between states Questions such as those from 24-33 in the terms of reference. The division into separate groups is necessarily arbitrary. While concentrating on the main topic devolved to them, groups should not worry unduly about overlap where that seems useful.

HACKUARIUM IS NOW COLLECTING KEY DISCUSSION POINTS AND ARGUMENTS

• your point/question/argument
• Ethics is Key!

..

Policy-Making has to do with Hacking/Doing/Making

THINKING-THROUGH-MAKING AND KNOWING-FROM-THE-INSIDE, some notes from | Tim Ingold -- Thinking through Making
Making through thinking in a manner of scientific experimentation and the design principles built on it is a way of knowing from the outside. It places the knowing outside the world oneself was used to know about. Thinking through making puts that relation in reverse. You SELF gets aligned with matter, living or not, through a transformation process, in which we perceive it, be-with it, learn through it... it is a learning process. It is a way of knowing from inside.
Here knowledge is not created through an encounter between minds already furnished with concepts and a material world already populated with objects but rather such knowledge grows from the crucible of our own practical and observational engagements with the materials, beings and things all around us in the very processes of thought.
So, this is a knowledge that doesn't wrap things up from the outside and enclose them with our knowledge. Rather it is a kind of knowledge that grows from the inside of being in the unfolding of life.
The problem with currently dominant ways of thinking in modern technoscience and in the kinds of policymaking that depends on modern technologies is that we have got the relation between knowing and being the wrong way around. That is why techno scientifically driven policy continues to deliver solutions that are unsustainable. By sustainability here we do not mean reaching some kind of steady state. but simply being able to carry on, not doing the same things but able to carry life on.
A lot of the spaces for modern policymaking make it increasingly difficult for people to carry on their lives by placing knowing on the outside of being, or by wrapping things up (blackboxing them) in our own preconceptions and categorical frameworks. We close them up leaving no room for « growth » (as in evolution, development, ideas to unfold naturally, from the inside).
By the same token, we cut knowing off from the immediacy of our own visceral sensory engagement with the world of our everyday lives. It seems that the more knowledgeable we become the less attention we pay to what is going on around us in our environment.
For example science is telling us a lot about climate change these days ... but the science does not encourage us to look very carefully at what's going around us going on around as it tells us the emissions of the graphs and tables and databases, so that we don't actually notice that there's something awfully wrong with the population of bees here in Britain, (and elsewhere.)
This is an example of the way in which an obsession with big science can actually stop us can pay attention to what is actually going on underneath our very noses. It has dumped information and dazzled us by images from screens, like in this lecture theaters which are darkened so we can't see what's going on outside or around us.
Policy-making including the thinking-through-making places the knowing inside the world oneself was used to know about. Thinking through making puts that relation in reverse. It is a way of knowing from inside.

(thoughts and notes from Tim Ingold by Vanessa Lorenzo)

QUESTION LIST

Advances in machine learning and genetic engineering are combining to produce rapid advances in medicine, development of materials and genetic engineering. Parallel advances in robotics and automation have made the practical process of gene editing scalable. The possibility exists that advances in quantum computing could further accelerate progress on machine learning, bringing a second boost to this technological rocket.
This Ditchley conference will bring together an unusual mix of deep expertise and scientific renown in the disciplines; thinkers on religion, ethics and law; investors fuelling innovation; and political leaders looking to shape the approach of society and state to fast emerging possibilities. We will attempt to establish sufficient common understanding of what the science promises and what it doesn’t and then explore the opportunities and risks that are likely to unfold at speed. This will be a first pass at preparation for potential blast off – what should be our moral, legal, economic and national security checklist as we wait on the launch pad of a new age?
The progress on machine learning is quite narrow in scope – deep learning using neural networks and other techniques on large data sets that now exist that didn’t previously and that are store-able and computable in a way that was not possible previously. But whereas progress towards general AI is often overstated, full general AI is not required to radically accelerate gene sequencing, editing and programming, with costs falling all the time and scale and speed increasing.
We will examine and try to come to preliminary conclusions on questions such as the following:
• Are we approaching a point of acceleration, perhaps even a point of no return, as these technologies converge? • How should the most aggressive genetic engineering technologies be regulated? What is the sliding scale of risk and potential benefit? How can societies best assess the ethical issues raised by these technologies to find an optimal balance between fostering genetic technologies for the common good while preventing abuse? • Can and should we distinguish between applications for inanimate materials, plants, animals and people? On the second day of the conference we will split into three groups to explore some of these questions more deeply from different perspectives. Each group will address the terms of reference as a whole but will also have some specific questions on which to focus. The questions for the groups should be viewed as a launchpad for discussion rather than as a tight constraint.

Group A

will look at the implications of these technologies from the perspective of the impact on health, personal identity, purpose and the relationship between groups of people in society. 1. Are these technologies converging in a powerful way with regard to individuals’ health, personal identity and relationships between people? 2. What further breakthroughs and regulatory latitude are needed for this to become transformational? 3. What are the implications of the automation of automation through techniques such as empirical computation? 4. What is the best approach to balancing data privacy and utility? 5. If we are able to find targeted genetic cures for diseases like cancer, then what will the impact be on the population and society? 6. What are the implications for ageing in particular, and what impact could this have on family structures and the care of children and elders? 7. How should we handle the implications of deeper knowledge about the influence of our genes on our characteristics and on the characteristics of groups? 8. How do we chart a course between remaining scientifically objective and providing material that could be misused to support racist conclusions by those tending to that view? 9. How do we prevent the possible emergence of a black market in genetic improvement of children? 10. More philosophically, how can we make sure the development of these technologies contributes to a positive sense of human progress and meaning, rather than to a sense of alienation and loss of purpose? 11. How can we manage the tension between science and religion as human capability to shape the genetic world increases? 12. What guidelines and regulation are required and how can they be best developed?

Group B

will look at the implications of these technologies with regard to national, economies, work, equality, society and democracy.
13. Are these technologies converging in a powerful way with respect to the economy and the nature of work and will there be implications for equality, society and democracy? 14. What further breakthroughs and regulatory latitude are needed for the development of these technologies to become transformational in their impact? 15. What are the implications of the automation of automation through techniques such as empirical computation? 16. What are the implications for personal data and privacy? Where and how will access to data confer advantage? 17. What kinds of jobs will become obsolete and what new kinds of jobs will be created by the development of these technologies and at what scales? 18. Will potential applications of the new technologies further intensify the concentration of wealth and power in a few hands? Will these technologies make the rest of industry more like the computer and software industry, with value primarily resting in intellectual property? 19. What industries will be most disrupted – for example health, pharmaceuticals, materials, farming, construction, manufacturing? 20. What are possible impacts on society, for example on the distribution of populations between cities and countries and the relationship between home and work? 21. How do economies change if more people are able to work more effectively for longer because of better health? 22. What happens to the ideals of democracies if we discover that one group of people is intellectually more developed than another or if we are able to make them so? 23. What guidelines and regulation are required and how can they be best developed?

Group C

will look at the implications of these technologies for competition and power struggles between states. 24. Are these technologies converging in a powerful way with respect to the relative power of states? 25. What further breakthroughs and regulatory latitude are needed for this to become transformational? Will relative power in deploying AI become a “singularity of power”, particularly when combined with bio-engineering prowess? 26. What are the implications in this context of the automation of automation, for example through techniques like empirical computation? What challenges does this pose for international regulation and oversight in particular? 27. Should this be compared to the space race of the Cold War? Will countries be tempted to pursue military applications either through bio-weapons or through the genetic improvement of military forces? 28. What new materials and techniques could emerge and how will they affect the balance of power in warfare? 29. Even if bio-weapons and the military enhancement of people were collectively agreed by the international community to be beyond the pale, what are the implications for national resilience (and therefore power) of healthier and more vigorous populations? 30. What are the implications for global politics of the concentration of AI power and bio- engineering power in the hands of two opposing super powers, the US and China? 31. Are there particular advantages for authoritarian and democratic capitalist states in pursuing these technologies? How will this affect the relationship between states and private sector companies leading in these technologies? 32. Should we expect an underdog’s playbook for mischief to emerge on AI and bio-engineering in the same way as it has on cyber capabilities in the hands of Russia, North Korea and Iran? 33. What international guidelines and regulation are both desirable and achievable given the current poor state of international coordination and multilateral fora?