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Susskind, 'A Manifesto for AI in the Law' ICAIL 2017, London, 2017

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Keynote address at the 16th International Conference on Artificial Intelligence and Law, June, London, including 15-point manifesto for the AI/Law research community.

Published in: Law

Susskind, 'A Manifesto for AI in the Law' ICAIL 2017, London, 2017

  1. 1. A Manifesto for Artificial Intelligence in the Law Professor Richard Susskind OBE 14 June 2017 @richardsusskind
  2. 2. four stages of acceptance
  3. 3. 1. This is worthless nonsense. (1986)
  4. 4. 2. This is an interesting but perverse point of view. (1996)
  5. 5. 3. This is true but quite unimportant. (2006)
  6. 6. 4. I have always said so. (2016)
  7. 7. 1980s case study AI Fallacy recently manifesto
  8. 8. 1980s
  9. 9. 1986
  10. 10. ‘Expert Systems in Law’ • A jurisprudential inquiry into AI in law • Exploring the limitations and implications • Built on consensus in analytical jurisprudence • A rule-based deductive model • Inspired by Hart, Raz, Harris, Kelsen, and others • ‘Clear cases of the expert domain’
  11. 11. case study
  12. 12. ‘Section 2 of this Act shall not apply to an action to which this section applies’
  13. 13. ‘a dense web of barely intelligible interrelated rules’
  14. 14. and yet of profound impact
  15. 15. ideal application area
  16. 16. the expert the knowledge engineer its function statute and case law self-knowledge
  17. 17. performance surprise memory no ‘off days’
  18. 18. 10 hours 10 minutes
  19. 19. more than 2 million paths
  20. 20. talked like a lawyer
  21. 21. in operation
  22. 22. 10 minutes later
  23. 23. feedback
  24. 24. what did we expect?
  25. 25. what have we got?
  26. 26. so why are there not more?
  27. 27. don’t judge too harshly
  28. 28. architectural vs functional
  29. 29. ‘using computer technology to make scarce expertise and knowledge more widely available and easily accessible’
  30. 30. nonetheless
  31. 31. law medicine tax audit consulting
  32. 32. costly to build no incentives the Web
  33. 33. 6 August 1991
  34. 34. hypertext / web
  35. 35. AI Fallacy
  36. 36. ‘there are lots of ways of being smart that aren’t smart like us’ Patrick Winston
  37. 37. AI Fallacy
  38. 38. ‘the mistaken assumption that the only way to develop systems that perform tasks at the level of experts or higher is to replicate the thinking processes of human specialists’
  39. 39. judgment
  40. 40. to what problem is judgment the solution?
  41. 41. uncertainty
  42. 42. can machines think?
  43. 43. increasingly capable non-thinking machines
  44. 44. second wave AI
  45. 45. hard-wired vs smart systems
  46. 46. recently
  47. 47. how should we feel?
  48. 48. manifesto
  49. 49. policy and aims for the AI and law research community for the coming decade (draft for discussion)
  50. 50. systems that undertake tasks that traditionally required human lawyers NB tasks not jobs
  51. 51. 15
  52. 52. 1. Social Purpose to use AI techniques and technologies to increase access to law and access to justice
  53. 53. Before the law stands a gatekeeper. A man from the country comes to this gatekeeper and requests admittance into the law. But the gatekeeper says that he cannot grant him admittance right now … The man from the country had not expected such difficulties; after all, he thinks, the law should be accessible to everyone at all times. (Kafka)
  54. 54. 2. Academic Orientation to develop and test new theories, techniques, methods, and systems
  55. 55. 3. Contribution to AI to contribute to work in the field of AI, especially through research into various forms of reasoning and problem-solving
  56. 56. 4. Contribution to Jurisprudence to explore traditional questions of legal theory using a new set of challenges and concepts
  57. 57. 5. Scope to focus on systems that engage in or support legislating, learning, advising, drafting, analysing, reasoning, and problem-solving
  58. 58. 6. Both Generations to engage in research into and development of both the first and second waves of systems
  59. 59. 7. Approach to maintain a multi-disciplinary orientation, involving (but not limited to) AI/law specialists, lawyers, legal theorists, computer and AI scientists, behavioural and cognitive psychologists
  60. 60. 8. Collaboration to work closely with those involved with innovating in legal practice and in the administration of justice
  61. 61. 9. Spirit to be bold and brave, pushing the boundaries, challenging – activists as well as theorists, but always sensitive
  62. 62. 10. Method to be unfailingly rigorous and responsible, rooted in robust theory and often in empirical evidence
  63. 63. 11. Public and Accessible to publish findings both as traditional scholarship as well as in forms that are accessible to non-technical audiences
  64. 64. 12. Commercial to provide a stream of innovations that are suitable for exploitation in the marketplace
  65. 65. 13. Thought Leadership to be the principal thought leaders in the field, based on rigour and research
  66. 66. 14. The Law of AI in the Law to identify and assess the legal implications of the technologies
  67. 67. 15. Ethics of AI in Law to articulate and debate the moral dilemmas that might arise from the technologies
  68. 68. finally
  69. 69. Stage Three Disruption Stage Three Disruption Stage Two Re-sourcing Stage Two Re-sourcing Stage One Denial Stage One Denial
  70. 70. ‘The best way to predict the future ...
  71. 71. … is to invent it’
  72. 72. richard@susskind.com @richardsusskind

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