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  1. 1. Will Robots Take Our Jobs? Socioeconomic Impacts of Intelligent Machines
  2. 2. Presented by Stani Meredith & Ed Messerly BITCA Faculty, Seattle Central College Special Thanks to Cliff Foster
  3. 3. Welcome to Henn na (Weird Hotel)
  4. 4. The Latest Numbers (as of Jan 16th 2016)
  5. 5. ● 7.1 million jobs could be lost through redundancy, automation, or disintermediation. ● Creation of 2.1 million new jobs, mainly in highly specialised areas such as computing, math, architecture, and engineering. ● Impacted countries include US, Australia, China, France, Germany, India, Italy, Japan, UK. ● Skills and jobs displacement will affect every industry and geographical region. ● Net loss of over 5 million jobs in 15 major developed and emerging economies by 2020 due to Technological Advances source: world economic forum executive summary 2016
  6. 6. source: world economic forum executive summary 2016
  7. 7. Drivers of Robotization
  8. 8. Technological Advances ● Moore’s “Law” Processor speeds and power will double every two years. ● Big Data, Cloud Based Analytics enable the affordable and accessible automation of numerous important aspects of data science, which businesses can leverage without understanding underlying algorithms. ● Quantum Computing harnesses the laws of quantum mechanics to process information. A traditional computer uses long strings of “bits,” which encode either a zero or a one. A quantum computer, on the uses quantum bits, or qubits rather than bits and thus can process vast number of calculations simultaneously.
  9. 9. ● Machine Learning A method of teaching computers to make and improve predictions or behaviors based on data (IBM’s Watson or Genetic Programming) ● Nanotech The study and application of extremely small things and can be used across all the other science fields. ● 3D Printing ● Biometrics and much much more...
  10. 10. Exponential Growth of Technology Image Source: http://uday.io/
  11. 11. Productivity ● Robots can perform tasks with greater repeatability and telemetry than humans. ● Robots are not prone to make mistakes and are more precise than human workers. ● Robots can produce a greater quantity in a short amount of time. ● Robots don’t need breaks or time off.
  12. 12. Corporate Savings ● Robots work faster and are more precious than humans. ● Robots don’t need to be paid or compensated for injuries. ● Robots are more accurate than humans and thus reduce waste of materials.
  13. 13. Safety ● Robots can perform jobs which are dangerous for humans. For example, robots will be used to cleanup in Fukushima’s radioactive waters (2017) ● Robots can lift heavy loads without suffering injuries or getting tired.
  14. 14. 2015 Investment in robotization ● $1.97+ billion in Acquisitions ● $42 million in a single IPO: ○ Corindus Vascular Robotics earned $42M for their IPO. ● $1.278+ billion in equity fundings (seed, crowd, series A,B,C,D, VC, etc) ● Unicorn Club investors show strong interest in robotization and AI. ● Investments have almost tripled from 2014.
  15. 15. Fewer workers needed to do the jobs due to accelerating automation In 2012, Google, for example, generated a profit of nearly $14 billion while employing fewer than 38,000 people. Contrast that with the automotive industry. At peak employment in 1979, General Motors alone had nearly 840,000 workers but earned only about $11 billion—20 percent less than what Google raked in. And, yes, that’s after adjusting for inflation. Martin Ford, Rise of the Robots
  16. 16. Highly standardized tasks are easily automatable ● Computers cannot evaluate like humans (yet), but the average human being uses evaluation approximately 5% of the time. ● Therefore, 95% of the time humans use highly standardized processes which are easily automatable.
  17. 17. Overview by Industry
  18. 18. Increasingly, machines are providing not only the brawn but the brains. Tyler Cowen
  19. 19. Service Sector Jobs Already Impacted include: Pharmacists Stockroom workers Home Assistants/Housekeepers Legal Assistants Financial Sector(automated trading)/Bank Teller/Mortgage Brokers/Accountants Amazon Prime Drone Delivery (video) Amazon Echo (video)
  20. 20. Farming - a case study “Vision Robotics, a company based in San Diego, California, is developing an octopus-like orange harvesting machine. The robot will use three-dimensional machine vision to make a computer model of an entire orange tree and then store the location of each fruit. That information will then be passed on to the machine’s eight robotic arms, which will rapidly harvest the oranges.” Martin Ford, Rise of the Robots
  21. 21. Automotive ● Driverless Cars: 10 million self-driving cars expected to be on the road by 2020 impacting all transportation related jobs.
  22. 22. Education ● MOOCs: Large-scale online education with fewer educators needed. Udacity, Coursera...and many more). Research shows that while many students enroll in MOOCs they don’t necessarily complete the course work. Not as far outreaching as initially thought. ● Machine Learning, adaptive learning, automated assessment, quantification of learning outcomes: More data equals better modeling. ● Robot Teachers: The Career and Technical Education Academy in Hutchinson, Kansas purchased a robot to incorporate into science, technology, engineering and math learning. ● University of Tokyo purchased 30 robots from Alderaban
  23. 23. ● Robots to Replace Native English Teachers in Korea. ● A Robot Teaches Calligraphy to Japan's schoolchildren. ● MIT’s Scratch Learning Programming Environment outteaches teachers. ● Automated Essay Graders - HP’s Kaggle ● “Intelligent”Tutors - Knewton ● What is a MOOC - video
  24. 24. Information Technology (Code writing code) ● Data Science: “Simply put, it’s the explosive rate of information growth that creates the requirement for narrow AI. Add to that the recent avalanche of user-generated content…and it’s clear that no organization (or human) can cope without the aid of narrow AI. “ David Senior ● Demand for software developers is at an all-time high but over time as more and more code is produced we can expect intelligent machines to learn how to perform new tasks and take over more programming jobs. ● Sysadmin jobs highly impacted. Near term solution: Learn how to program automated systems.
  25. 25. ● One of DARPA’s projects focuses on using software to assemble code from existing code bases....”Many programmers today focus more on assembling code from resources such as StackOverflow.com, instead of re-creating code that already exists...and DARPA has automated that process. “ Grant Gross, IDG NewsService ● Websites creation standardized process can be easily automated. ● Mobile industries expect employment growth, however approximately 40% of the skills required in the industry are not yet part of the core skill set of these functions today.
  26. 26. ● Trend towards lower salaries for most IT professionals as automation takes over an increasing number of tasks and reduces the need for traditional education ● Appypie: Android picture based, drag and drop “coding.”
  27. 27. Journalism and Blogging (case study) ● Consider a company call Narrative Science founded by researchers from Northwestern University. They discovered that they could develop software that can write basic sports stories. I've read a few of those stories, and although they're not brilliant, they're serviceable -- probably good enough to cover small-town sports….In 2013, Narrative Science's software produced nearly 400,000 accounts of Little League games. Last year it was expected to crank out 1.5 million… The software also produces stories on corporate earnings -- usually quite basic, but good enough to give investors a quick read on the market and do it much faster than even an experienced business writer can. Bill Snyder, Tech’s Bottom Line
  28. 28. Other industries impacted ● Healthcare: Data-driven insights, medical records, order entry, and decision support. 3D organ models, elderly care robotization (especially in Japan) ● Military: Drone Military, Cyber warfare ● Police: Crime-Fighting Robots Go On Patrol In Silicon Valley ● Science: The Cancer Genome Atlas uses AI and Physics to beat breast cancer ● Creative Robots: Google’s Deep Dream ● Sports & Entertainment: IBM’s Watson, Drone racing championships, Chess, Go playing robots, better than humans
  29. 29. Humanoids Humanoid robots use human tools and are better than humans at operating these tools in the home or workplace.
  30. 30. Socioeconomic Impacts
  31. 31. Techno-Feudalism or Techno-Optimism?
  32. 32. It’s up to the humans (as of now!!!)
  33. 33. Proposed Solutions
  34. 34. Education and Work arrangements ● Leveraging flexible working arrangements and online talent platforms (sharing economy job - no benefits, no work rules) ● Rethinking education systems. ● Incentivizing lifelong learning. ● Cross-industry and public-private collaboration.
  35. 35. ● But wait...won’t robotization also create jobs? Yes, but they will be sharing economy jobs. ● The Luddite argument: Stop the process or robotization. No way. It is unstoppable.
  36. 36. Political Action leading to a Humans First world "Absent appropriate fiscal policy that redistributes from winners to losers, smart machines can mean long-term misery for all," Boston U's Seth Benzell, Laurence Kotlikoff, and Guillermo LaGarda, and Columbia U's Jeffrey Sachs ● Global Technology Tax ● Universal Basic Income ● Regulation - easy to get around. ● Include (give voice) to diverse demographics in the building of AIs
  37. 37. Robot Rights Is it ethical to discriminate against robots? Yes, so long as the machine is a machine and not a sentient being.
  38. 38. Transhumanism
  39. 39. Transhumanism Transhumanists reason that we can, and should, improve the human condition through the use of advanced technologies such as genetic engineering, nanotech, cloning, and other emerging technologies. Transhumanists are interested in life extension and in boosting our physical, intellectual, and psychological capabilities beyond what humans have naturally evolved to be capable of.
  40. 40. For example, Transcranial direct current stimulation (TDCS) speeds up reaction times and learning speed by running a very weak electric current through your brain. This technology has already been used by the US military to train snipers. Transhumanism also deals with the fascinating concept of mind uploading to a computer, and what might happen as we reach the Technological Singularity.
  41. 41. Superintelligent Machines (AGIs)
  42. 42. How likely? “We need only continue to produce better computers—which we will, unless we destroy ourselves or meet our end some other way. We already know that it is possible for mere matter to acquire “general intelligence”—the ability to learn new concepts and employ them in unfamiliar contexts—because the 1,200 cc of salty porridge inside our heads has managed it. There is no reason to believe that a suitably advanced digital computer couldn’t do the same. “ Sam Harris
  43. 43. The human error factor “Picture ten young men in a room—several of them with undiagnosed Asperger’ s—drinking Red Bull and wondering whether to flip a switch. Should any single company or research group be able to decide the fate of humanity? The question nearly answers itself.” Sam Harris
  44. 44. The Singularity is near The Technological Singularity is a term coined by John Von Neumann and popularized by Ray Kurzweil. It is the digital version of a black hole - an event caused by the intelligence explosion of AGIs, surpassing human intelligence to the point where AGIs would be capable of progressive self-improvement resulting in ever smarter and more powerful machines and leading to a singularity point beyond which events may become unpredictable or beyond the comprehension to human intelligence.
  45. 45. AGI: Friend or Foe? ● "It would take off on its own, and re-design itself at an ever increasing rate... Humans, who are limited by slow biological evolution, couldn't compete, and would be superseded." Stephen Hawking ● Highly influential tech entrepreneur Elon Musk has warned that AI is "our biggest existential threat". ● AGIs could solve currently unsolvable problems in chemistry, physics, computer science or mathematics. ● “Will robots inherit the earth? Yes, but they will be our children.” Marvin Minsky
  46. 46. Nick Bostrom’s famous paper clip example But, say one day we create a super intelligence and we ask it to make as many paper clips as possible. Maybe we built it to run our paper-clip factory. If we were to think through what it would actually mean to configure the universe in a way that maximizes the number of paper clips that exist, you realize that such an AI would have incentives, instrumental reasons, to harm humans. Maybe it would want to get rid of humans, so we don’t switch it off, because then there would be fewer paper clips. Human bodies consist of a lot of atoms and they can be used to build more paper clips. If you plug into a super-intelligent machine with almost any goal you can imagine, most would be inconsistent with the survival and flourishing of the human civilization.
  47. 47. Open questions for the inquiring mind ● How can we tell if a computer program is an AGI? ● Are even humans self aware for the majority of their lives? Then should self awareness be the measure for an AGI? If not, what else? ● Is it the computer or the program that is a person? Or are they both the person? ● Once an AGI program is running on a computer would be murder to shut it off? ● An AGI program can be easily copied on multiple computers. Are those identically functioning programs the same person or many different people? ● Do the AGI get to vote? With copied versions, do they they get one vote, or many?
  48. 48. ● What if, due to a human error (coding bug) a programmer creates billions of different AGIs? Are they are still people with rights? ● What set of values would an AGI have and how would they track with human values? Would human’s middle size, linear mind even be able to comprehend? ● Have the AGIs already arrived without us knowing it?
  49. 49. Sources and Further Reading Suggestions
  50. 50. Articles and Publications: http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf https://aeon.co/essays/how-close-are-we-to-creating-artificial-intelligence http://www.ifr.org/industrial-robots/statistics/ http://www.therobotreport.com/news/2015-fundings-ipos-and-acquisitions http://sanfrancisco.cbslocal.com/2014/11/18/crime-fighting-robots-go-on-patrol-in-silicon-valley-k5-knightscope- mountain-view-stacy-stephens-autonomous-security-guard/ http://www3.weforum.org/docs/WEF_FOJ_Executive_Summary_Jobs.pdf http://motherboard.vice.com/read/simulated-universe-thinker-nick-bostrom-hasnt-stopped-believing http://www.extremetech.com/extreme/152240-what-is-transhumanism-or-what-does-it-mean-to-be-human
  51. 51. http://www.technologyreview.com/news/545561/fukushima-robot/ http://techcrunch.com/2013/11/02/welcome-to-the-unicorn-club/ https://uwaterloo.ca/institute-for-quantum-computing/quantum-computing-101 http://data-informed.com/automation-new-reality-for-big-data-initiatives/ http://www.nano.gov/nanotech-101/what/definition http://data-informed.com/automation-new-reality-for-big-data-initiatives/#sthash.BEO32TVz.dpuf
  52. 52. http://www.computerworld.com/article/2692377/enterprise-software/the-future-of-artificial-intelligence-will- computers-take-your-job.html https://www.insidehighered.com/blogs/hack-higher-education/top-ed-tech-trends-2012-automation-and-artificial- intelligence https://www.insidehighered.com/blogs/hack-higher-education/top-ed-tech-trends-2012-automation-and-artificial- intelligence http://www.samharris.org/blog/item/can-we-avoid-a-digital-apocalypse http://www.amazon.com/Rise-Robots-Technology-Threat-Jobless/dp/1480574775 http://www.amazon.com/Superintelligence-Dangers-Strategies-Nick-Bostrom/dp/1501227742 https://www.youtube.com/watch?v=VBceREwF7SA
  53. 53. Image Credits Ranks of robot women (Shutterstock.com) http://www.controversomagazine.com/english/human-evolution-and-transhumanism-in-science-fiction/ https://www.robots.com/articles/viewing/benefits-of-robots Bloomberg Ex Machina
  54. 54. Q&A and Discussion