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AI & Business - Opportunities & Dangers

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A review of some of my thoughts on AI in the enterprise.

Published in: Technology
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AI & Business - Opportunities & Dangers

  1. 1. AI & Business Opportunities and Dangers Will Murphy @willmurphy Talla.com
  2. 2. MY BACKGROUND 2 2001 – 2016 FedEx 2016 Pioneer in the use of cross- company APIs to create new platforms Pioneer in the area Intelligent Agents. Pioneer in the area of IoT Sensor-based logistics. FedEx IT Corporate Entrepreneur Startup Entrepreneur API Connect companies via tech Connect physical/ digital worlds Create new intelligent agents that connect people and machines
  3. 3. MY BACKGROUND 3
  4. 4. MY BACKGROUND 4 This is a presentation for executives and entrepreneurs. I’m not an A.I. expert exploring innovation. I’m an innovation expert exploring A.I.
  5. 5. Overview Dangers Opportunities
  6. 6. WHAT IS A.I. ? 6 Artificial Intelligence (A.I.) A branch of computer science focused on getting computers to exhibit intelligence. Machine Learning A set of techniques for computers to have cognitive functions. Deep Learning Successful Machine Learning techniques that use Neural Nets with additional layers (deep).
  7. 7. WHAT IS A.I. ? 7 A.I. A branch of computer science focused on getting computers to exhibit intelligence. Machine Learning A range of techniques for computers to have cognitive functions. (Mainly pattern recognition and prediction.) Deep Learning Type of Machine Learning that uses Neural Nets with additional layers (deep). (Accurate and productive) Applied A.I. technology Pattern Recognition & Prediction Which leads to… Perception, insights, decisions, automation What we are usually discussing: Narrow A.I. (focused)
  8. 8. ALPHAGO: UNMASKED INTELLIGENCE 8 Sources: http://arstechnica.com/information-technology/2017/01/alphago-is-back-and-secretly-crushing-the-worlds-best-human-players/ http://www.wsj.com/articles/ai-program-vanquishes-human-players-of-go-in-china-1483601561 “After humanity spent thousands of years improving our tactics, computers tell us that humans are completely wrong,” Mr. Ke, 19, wrote on Chinese social media platform Weibo after his defeat. “I would go as far as to say not a single human has touched the edge of the truth of Go.”
  9. 9. TECH IS DOMINATING
  10. 10. TECH IS DOMINATING
  11. 11. Data is the oil that fuels A.I.
  12. 12. A.I. IS THE TECH FOCUS RIGHT NOW 12 "It’s the first inning. It might even be the first guys up at bat. We're on the edge of the golden age [of A.I.].” - Jeff Bezos, CEO, Amazon “In the long run, I think we will evolve in computing from a mobile-first to an A.I.-first world.” - Sundar Pichai, CEO, Google
  13. 13. THE INTELLIGENT AUTOMATION AGE 13 The Web connects millions of people. The Internet becomes more social, creating networks of people. Mobile + Internet + social capabilities – create networks of people. Collaborative commerce begins. CONNECTED 1995 SOCIAL 2005 COLLABORATIVE 2010 INTELLIGENT AUTOMATION 2015 Intelligent automation augments humans then replaces them.
  14. 14. TRANSITIONING TO THE INTELLIGENT AUTOMATION AGE 14 CONNECTED 1995 SOCIAL 2005 COLLABORATIVE 2010 INTELLIGENT AUTOMATION 2015 Hybrid UI Mobile Interface Browser The Web connects millions of people. The Internet becomes more social, creating networks of people. Mobile + Internet + social capabilities – create networks of people. Collaborative commerce begins. Intelligent automation augments humans then replaces them. A.I. Smart Phone Web Interface Tech
  15. 15. Overview Dangers Opportunities
  16. 16. More intelligence, More problems A.I. dangers
  17. 17. 19 EXISTENTIAL DANGERS Optimization without humanity Too much like humanity (but more powerful)
  18. 18. 20 EXISTENTIAL DANGERS Optimization without humanity Too much like humanity (but more powerful) But, I don’t want to talk about that. Let’s talk about business dangers that will happen sooner.
  19. 19. DATA MONOPOLIES
  20. 20. DATA MONOPOLIES 22 Data * Processing * Talent Do we need data neutrality?
  21. 21. POTENTIAL SOLUTIONS 23 Decentralization: • Build policies that encourage decentralization of data • Blockchains for data decentralization? Data Valuation Statement Tax (Will cover proposal later) • Retained data could be taxed at an increasing rate (more data, more tax)
  22. 22. A.I. Overview & Issues Dangers Opportunities
  23. 23. 25 A.I. IN BUSINESS Legal Health Marketing & Sales Transportation Finance Customer Service Security Office Workflow Automation Decisions, actions, communication, and insights
  24. 24. DATA ABRITRAGE Opportunities created by data being worth different amounts in different contexts.
  25. 25. 27 DATA VALUATION MODEL Time Value Legal Constraints Context Value Quality Access Training Value New: Data Valuation Statement
  26. 26. 28 RECOMMENDATIONS FOR ENTERPRISE Create Your Data Resources Strategy Data Value Model Design products that learn Look For Valuable Data Sets (Sell, Data Arbitrage) Create ideas using Sense & Respond Utilize your Innovation & Data Science Groups Utilize Networked A.I. A.I. strategy is just part of your business strategy and data strategy
  27. 27. 29 AI SENSE & RESPOND FRAMEWORK Predict operational challenges Which customers are the best? What text performs the best upsells? Find future customers, predict optimal marketing Optimize processes, identify experts Pattern Recognition Prediction Operational Efficiency Generate Revenue Notify experts when an operational challenge is predicted. Automatically contact best customers and upsell using the optimal text. Automation SENSE (Perception, insights, decisions) RESPOND (Actions)
  28. 28. 30 Where technology and A.I. is headed It will the water we will swim in.
  29. 29. Will Murphy @willmurphy Talla.com sales@talla.com Thank You!

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