AI and the Future of Innovation - Daniel Hulme, Satalia
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The document is a presentation by Daniel Hulme, CEO of Satalia, about AI and the future of innovation. Some key points from the presentation include: - AI can enhance decision making by providing data, information, knowledge, understanding, and wisdom. - As AI systems advance, they will be able to perform more complex tasks like predicting outcomes, interpreting knowledge, utilizing understanding, and developing wisdom. - Properly developing and governing AI will require a focus on security, safety, explainability, transparency, and ethics. - Innovation trends show organizations shifting away from hierarchies toward networks, distributed decision making, transparency, and focusing on talents and mastery over job titles. - The future may bring technological
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AI and the Future of Innovation - Daniel Hulme, Satalia
- 1. MASTER CLASS Daniel Hulme CHIEF EXECUTIVE OFFICER SATALIA AI and the Future of Innovation LONDON, UNITED KINGDOM ~ SEPTEMBER 1 - 2, 2022 DIGIMARCONUK.CO.UK | #DigiMarConUK
- 2. About me Entrepreneur in Residence @ UCL Director of Business Analytics MSc Lecturer in AI and Innovation @ UCL & LSE Postdoc in Innovation and Technology Transfer PhD in Artificial Intelligence MBA Electives London Business School MSci in Artificial Intelligence Chief AI Officer @ WPP CEO @ Satalia Advisor to UAE AI Strategy Co-founder of the Faculty AI Advisor to Syntropy, e-Numeracy and others Kauffman Global Scholar Startup mentor and speaker 2
- 7. JOHN READ THE LETTER TO MARY
- 8. Data Driven Decision Making WISDOM UNDERSTANDING KNOWLEDGE INFORMATION DATA = symbols = contextualized DATA
- 9. Prediction 9
- 10. Data Driven Decision Making WISDOM UNDERSTANDING KNOWLEDGE INFORMATION DATA = symbols = contextualized DATA = organised INFORMATION
- 11. Prediction 11
- 12. Data Driven Decision Making WISDOM UNDERSTANDING KNOWLEDGE INFORMATION DATA = symbols = contextualized DATA = organised INFORMATION = interpreted KNOWLEDGE
- 13. Data Driven Decision Making WISDOM UNDERSTANDING KNOWLEDGE INFORMATION DATA = symbols = contextualized DATA = organised INFORMATION = interpreted KNOWLEDGE = utilised UNDERSTANDING
- 14. Decision Making
- 15. 2 x 2
- 16. 14 x 768
- 17. Decision Making
- 18. Resource Allocation RULES Flying right of walking Swimming left of walking Reptiles 2-away from felines No same colours touching Tails prefer next to tails Males prefer near females
- 19. Resource Allocation 120 RULES Flying right of walking Swimming left of walking Reptiles 2-away from felines No same colours touching Tails prefer next to tails Males prefer near females
- 20. Resource Allocation RULES Flying right of walking Swimming left of walking Reptiles 2-away from felines No same colours touching Tails prefer next to tails Males prefer near females
- 21. Resource Allocation 1,307,674,368,000 RULES Flying right of walking Swimming left of walking Reptiles 2-away from felines No same colours touching Tails prefer next to tails Males prefer near females
- 23. 500! ≈ 1e+1134
- 27. Transportation Problems # ROUTES 1,000,000 PER SECOND 10 3,628,800 4 seconds 11 39,916,800 1 minute 13 6,227,020,800 2 hours 14 87,178,291,200 1 day 16 20,922,789,888,000 1 year 20 2,432,902,008,176,640,000 77,000 years 22 1,124,000,727,777,610,000,000 36 millennia 24 620,448,401,733,239,000,000,000 20B years
- 28. Automation ACTION INSIGHT DATA Prescriptive analytics ● Optimisation ● Decision-science Predictive analytics ● Data-science ● Machine learning Descriptive analytics ● Contextualisation ● Data visualisation Data Engineering ● Infrastructure ● Data assimilation WISDOM UNDERSTANDING KNOWLEDGE INFORMATION DATA
- 29. ACTION INSIGHT DATA ADAPT Intelligence Goal-directed Adaptive Behaviour Sternberg & Salter Artificial Intelligence
- 31. Prediction (Data, Information, Knowledge)
- 33. Artificial Intelligence Artificial General Intelligence bounds of human ability Artificial Intelligences
- 34. Artificial Intelligence Artificial General Intelligence Super Intelligence bounds of human ability Artificial Intelligences
- 36. AI Security, Safety, Ethics and Governance AI Security Authentication Accessibility Anonymity AI Safety Transparency Explainability Auditability AI Ethics Intent Objectives Constraints AI Governance Accountability Change management Decision-making
- 37. Innovation
- 38. Hidden dynamics in hierarchy
- 39. Being Lean
- 40. 8 Important Trends (Corporate Rebels) 1. Profit → Purpose & values 2. Hierarchical pyramid → Network of teams 3. Directive leadership → Supportive leadership 4. Plan & predict → Experiment & adapt 5. Rules & control → Freedom & trust 6. Centralized authority → Distributed decision making 7. Secrecy → Radical transparency 8. Job descriptions → Talents & mastery
- 41. Innovation, Motivation and Purpose “Creativity that ships” Steve Jobs “Motivation is the Energy for Action” Edward Deci “Autonomy, Mastery, Purpose” Dan Pink, Drive “Time is the new money” Richard Branson The rise of the purposeful company DATA SCIENCE CLOUD COMPUTING OPEN (BIG) DATA ARTIFICIAL INTELLIGENCE TALENT
- 43. Talent Strategy No Talent Industry Sexiness Challenging Problems
- 44. Talent Strategy Sticky Talent No Talent Industry Sexiness Challenging Problems
- 45. Talent Strategy Talent Churn Sticky Talent No Talent Talent Churn Industry Sexiness Challenging Problems
- 46. Talent Strategy Talent Churn Sticky Talent No Talent Talent Churn Industry Sexiness Challenging Problems
- 48. Strictly Confidential Organisational Network Analysis
- 49. Swarm diagrams provide transparent data on activity across network tools. Interactive network diagrams show relationships and the flow of information from and to the worker. Swarm diagrams show the significance of points and the weight of opinion compared to the suggestions received by others within the organisation.
- 50. Digital Transformation, Twins, Consciousness
- 51. The Future
- 52. Investment into AI https://medium.com/politics-ai/an-overview-of-national-ai-strategies-2a70ec6edfd the nation that leads in AI 'will be the ruler of the world'
- 53. PESTEL of Singularities Political - when we no longer know what is true Economic - when we automate the majority of human labour Social - when we cure death Technological - when we create a Superintelligence Environmental - when we trigger uncontrollable ecological collapse Legal - when surveillance becomes ubiquitous
- 54. Political - when we no longer know what is true
- 55. Economic - when we automate the majority of human labour
- 56. Social - when we cure death
- 57. Technological - when we create a Superintelligence
- 58. Environmental - uncontrollable ecological collapse - Environmental and technological risks continue to rise - Geopolitical and societal risks are stable but remain high - Economic risks perceived as low both in likelihood and impact - Environment-related risks again lying in the higher-impact - Top likely global risks are extreme weather events - Previous years respondents to the GRPS tended to be optimistic about technological risks, this year’s concerns jump - Cyber attacks rank 3rd global risks in both likelihood and impact - Data fraud and theft rank as 4th global risks in terms of likelihood - Geopolitical risks expect to worsen due to political and economic confrontations/frictions between major powers - Most interconnected risks were “adverse consequence of technologies” and “unemployment and under-employment”, both highly connected with “profound social instability”
- 59. Legal - when surveillance becomes ubiquitous 59
- 60. Purpose and Vision Everyone free to live beyond themselves
- 61. Daniel Hulme daniel@satalia.com www.satalia.com +447773765097 @TheSolveEngine Connect with me on LinkedIn Questions