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Ai morality-today-2018-web

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Slides from talk given to the Adelaide Chapter of Reasonable Faith. The video is available at https://www.youtube.com/watch?v=SQYPaLR_NbE

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Ai morality-today-2018-web

  1. 1. AI Implications and Ethics Today (Tom Daly 2018) A brief introduction to the status of AI and consideration of some of the current ethical questions.
  2. 2. GOALS Start conversations • within the “C”hurch to raise awareness. • (in part) use AI to highlight that we would all benefit if science and technology would embrace rather than exclude theological considerations
  3. 3. Agenda 1. Introduction to AI 2. Implications of AI – Economic / societal – Direct Ethical considerations – Risks 3. Implications from the future “today” 4. Initial thoughts on how to respond
  4. 4. AI Introduction
  5. 5. AI Introduction Definition Artificial Intelligence is intelligence displayed by machines, in contrast with the natural intelligence (NI) displayed by humans and other animals. Machine Learning gives computers the ability to learn without being explicitly programmed. (Arthur Samuel 1957)
  6. 6. • Image recognition & processing (c.f. human sight) • Speech recognition – natural language processing • speech to text <-> text to speech • language translation • Rudimentary Spatial awareness – via imaging and radar etc – Boston Dynamics robot arms for examples. • Rudimentary modeling – prediction AI Introduction some important components – that are part of overall AI “progress”
  7. 7. AI is today Far broader than just (ro)bots • Junk mail filtering • Credit Card companies : fraud detection • Hiring/recruiting • Driverless cars • Electronic assistants : Siri, Alexa Cortana etc • Google search • Facebook,Google, advertising, marketing etc • Medical (reading scans, images, diagnostics, surgery and more ... ) • Boston Dynamics, • Amazon Go : cashless supermarkets • Cloud (early) : AI used to spot and fix/manage operational errors • Face recognition – fun e.g. photos on your laptop/facebook – anti-terror and policing uses, for tracking people. – major crimes ? • Uber/Lyft – ML for pricing • Navigation (maps) • Financial modeling / stock market trading • Loan approving / credit risk • Speech recognition • Language translation • Text to Speech • Battlefield and Warfare (LAWs) • Image recognition • Game playing – Watson – chess , AlphaGo and AlphaGo Zero => watershed moment! • Legal/Paralegal • Crime fighting – modeling / prediction And so much more ! customer service BOTS ?
  8. 8. AI is already causing changes
  9. 9. AI Today – Examples Amazon Go , Bingo Box https://technode.com/2017/09/28/bingobox-unveils-new-ai-tech-for- its-unmanned-stores BingoBox • fast moving consumer goods • cheaper (?) • like automated OTR
  10. 10. AI Today – Example Medical Imaging • IBM Deep learning => identifying tuberculosis with 96 percent accuracy • IBM Deep Patient => predict disease given a patient's medical records. The application proved to be considerably better at forecasting disease than physicians—even for schizophrenia. https://www.ibm.com/developerworks/library/cc-beginner-guide-machine-learning-ai- cognitive/index.html Smart Phone apps https://iq.intel.com/skin-cancer-detection-using-artificial- intelligence/?sf181438035=1 • initially 10,000 photos • looking for 100 of thousands more How many images/patients could a dermatologist view in their lifetime ? How does the medical professionals role change in light of this “type” of application?
  11. 11. AI Today – Example Mortality prediction • for end of life (so can die at home) • predict sudden death => intervention https://spectrum.ieee.org/the-human- os/biomedical/diagnostics/stanfords-ai-predicts-death-for-better-end- of-life-care University of Adelaide have developed an AI that can analyze CT scans to predict if a patient will die within five years with 69 percent accuracy.
  12. 12. • Computing power (enables Deep Neural Networks) • Moore’s law , GPUs , (soon Quantum) • Large Super Computers -> PC -> Cloud • Democratization of Tools and Techniques • Availability of large data sets (many for free) • IOT (cameras , sensors, cars , phones … ) • facebook, google … • scientific: SKA to capture 1ZB data/6 hrs AI Today – why now Computing power and big data computing power increasing exponentially
  13. 13. AI Today – why now Collaboration / neuroscience advances Internet and globalisation  sharing of information , building on progress  C.F. Human gnome project where collaboration was key Advances in neuroscience • advances in imaging • AI adopting discoveries and models from neuro and cognitive sciences https://www.technologyreview.com/video/609389/understanding-intelligence/
  14. 14. AI Today – why now M-O-N-E-Y ! Follow the Money  China  US Tech Companies  Facebook, AWS, Google , Oracle, IBM Microsoft and many many more  huge venture capital => drives innovation  Defence and Govt agencies https://www.forbes.com/sites/louiscolumbu s/2018/02/18/roundup-of-machine- learning-forecasts-and-market-estimates- 2018/#13c9280d2225 ML patents grew at a 34% (CAGR) between 2013 and 2017, the third- fastest growing category of all patents granted. IDC: spending on AI and ML will grow from $12B in 2017 to $57.6B by 2021. Deloitte Global: #of machine learning pilots and implementations will double in 2018 compared to 2017, and double again by 2020
  15. 15. Existing Technology AI Continuum Automation /Robotics AI , Deep Learning DNN time Human level AGI Super Intelligence Intelligence unknown time assumed to happen quickly we are here Still a huge gap
  16. 16. AI Implications
  17. 17. Areas of Implications of AI Economic/social Ethics Use of AI • Significant job loss and structural change • UBI • impact on developing countries • Who owns assets E.g. Uber • Meaning / Purpose without employment Good Bad Intrinsic Risks • legal responsibility for AI • AI goals/value encoding • Biases (e.g. racial) • black box problem • Augmentation • Cure diseases • climate and ecology • solve energy issues • reduce road toll • ease poverty(?) • assisted living • AI assisted research • autonomous weapons • Replacement for “beating heart”? • Sex robots/Deep fakes • catastrophic failure • AI arms race • govenment misuse • new security threats • SuperIntelligence Alignment problem / loss of control • investment in AI power not risk mitigation Theological/Philosop hical (Super Intelligence) • create god(s) • become god(s) • alignment issues • justice • freewill • mercy • morality • agency • what does it mean to be human? • mind or matter first • machine rights • charity/empathy/compa ssion • moral to stop it / kill it ? • consciousness • Implications for Christianity
  18. 18. Employment / Economic implications Job losses just from transport are potentially signifcant ! http://www.abc.net.au/news/2017-03-11/everything-you-need- to-know-about-driverless-cars/8336322 Highly automated 2020 Fully automated next decade (i.e. 2020’s) Society of Automotive Engineers/VicRoads Robotaxi permit gets Arizona’s OK; Waymo will start service in 2018 Insurance industry is “very aware” and preparing for massive change
  19. 19. Employment / Economic implications significant loss of employment over broad range – looking likely From MIT where there is a HUGE investment into AI research and robotics http://www.abc.net.au/news/2017-08-08/could-a- robot-do-your-job-artificial-intelligence/8782174 Feb 2018 NAB announced 6000 job losses due entirely to automation ABC Website has some good analysis on AI and jobs
  20. 20. World Economic Forum • USA Med students start with $300K debt , but if AI is doing better diagnostics than doctors, then try paying that off as a yoga teacher. • In Germany robots have effectively blocked many from entering the manufacturing field, instead higher numbers go straight into service jobs. • global management consultants McKinsey “More than a fifth of the global labour force - 800 million workers - might lose their jobs because of automation.” Oxford University academics Carl Frey and Michael Osborne, • 47 percent of jobs in the US were at high risk of being automated OECD : • 10% job loss but significant structural change in many jobs . World Bank : • World Bank Group President Jim Yong Kim says the world is a on a "crash course" Employment / Economic implications Number of jobs lost to AI is debated, the fact of Job loss and change in not.
  21. 21. Offshoring took jobs and placed them in developing countries What happens now that workers in developing countries are competing with AI and robots in richer countries ? E.g. Call centres • jobs reduced by AI bots (text and voice) • potential for cost savings is large i.e. $/day is starting to look expensive Employment / Economic implications Developing Countries BOTS • don’t need a break • can work 24*7 • get sick or need health care • scale cheaply • get cheaper with more work • are owned by the rich • can have the right “voice”
  22. 22. • Once heard a sermon from Tim Costello where he referred to work as “occupational therapy” as it is closely tied to identity and often personal value • Universal basic wage or universal basic income is appearing in the mainstream media. • Who owns assets ? – e.g. Uber for instance – Robot Tax c.f. land tax Employment / Economic implications Compare Industrial revolution => societal change Job losses and displacement from AI and automation are already happening, perhaps it is just change but what if it is more than that ? What is the meaning of work ?
  23. 23. Ethics
  24. 24. Ethics in use of AI beneficial uses of AI : some examples • reduce road toll – approx 36,000 deaths in the US , 1200 in Australia in 2017 • enable discovery of cures for diseases – Cancer and disease screening set to be vastly more reliable – AI may discover answers to medical questions we haven’t yet asked • Assisted living (disabled, elderly) • Assist developing world – AI and chatbots gathering data, directly assisting people Is there a “moral obligation” to pursue AI because of the suffering it could alleviate ? Stanford research IBM investment World Bank Blog
  25. 25. Note the personalisation and the use of “I” and “we” pronouns Are we fooling ourselves ? Do people in need … need a machine ? Ethics in use of AI bad (or at least questionable) uses of AI : woebot on FB messenger
  26. 26. Ethics in use of AI Bad uses of AI • AI arms race – Intelligence itself can yeild power => AI arms race to AGI https://motherboard.vice.com/en_us/article/xywmyk/a-global- arms-race-to-create-a-superintelligent-ai-is-looming • Lethal Autonomous Weapons (LAWs) – Imagine a “drone” which learns who, what, when to attack with no human control. – What about swarms of autonomous drones – Many countries are developing LAWs http://time.com/4948633/robots-artificial-intelligence-war/ Remember a LAW is likely “writing or modifying its own code or data ” Boston Dynamics have a range of ever more capable AI robots
  27. 27. • AI powered sex robots • Deepfakes Porn / Child Porn Ethics in use of AI bad uses of AI : impact on human sexuality WikiPedia : Deepfake, a portmanteau of "deep learning" and "fake",[1] is an artificial technique. It is used to combine and superimpose existing images and videos onto source images or videos. Deepfakes may be used to create fake celebrity pornographic videos or revenge porn.[2] Deepfake pornography surfaced on the Internet in 2017, particularly on Reddit,[3] and has been banned by sites including Reddit, Twitter, and Pornhub.[4][5][6] Deepfakes can be used to create fake news and malicious hoaxes.[7][8]
  28. 28. Moral/Ethical implication #3 • Today AI used (increasingly) for hiring decisions – What if the AI has indeed learned who is the “best person for the job” , do we need to re-examine our definition of best? • Another example: credit rating in the US – racial bias built into the data, but it is data ! Ethics : Intrinsic Example : decision making HR Great example of challenges of goal alignment => we had better be honest, but also who chooses ?
  29. 29. Moral/Ethical implication #3 • Example : AI used to determine/assist recidivism risk i.e parole / bail  Good, because it is well known that human factors can negatively influence outcomes (e.g. prior to lunch, after lunch variation)  Challenging because how do we know the basis of a decision ?https://www.nytimes.com/2017/05/01/us/politics/sent-to-prison-by-a-software- programs-secret-algorithms.html • Example: a particular classifier engine classifies “husky dog” as wolf but never actually gave weight to the part of the image that was the dog. Ethics : Intrinsic decision making , black box problem Black-Box problem: not possible to understand the AI’s decisions/results Is there some human “uniqueness” needed ?
  30. 30. Risks
  31. 31. • Catastrophic failure – c.f. nuclear weapons • New AI based cyber attacks – MicroSoft using VR to “test” advanced AI’s against “attack” – “indeed, the big takeaway of the report is that AI is now on the cusp of being a tremendously negative disruptive force as rival states, criminals, and terrorists use the scale and efficiency of AI to launch finely-targeted and highly efficient attacks” Risks https://www.gizmodo.com.au/2018/02/new- report-on-ai-risks-paints-a-grim-future • Oxford “Future of humanity institute” • Cambridge “Centre for study of existential risk” • EFF (electronic frontiers foundation) • OpenAI Stuxnet
  32. 32. • Investment – Money going into AI power not risk mitigation both • Human influences – Microsoft Tay chatbot • Courts and evidence – fake audio, fake video Risks ABC Website 4th March 2018 Scientific American
  33. 33. Nudge Theory / pursasion – AI chatbots already suspected of influencing political opinions via social media (c.f. subliminal adverstising on steroids) – 2017 Veritas Forum at Brown : “ Can Robots Become Human” https://www.youtube.com/watch?v=tbUnMhod_A0 – Guardian Science Weekly podcast on AI from 2017 Risks
  34. 34. Risks "We've deployed new AI tools that do a better job of identifying fake accounts that may be trying to interfere in elections or spread misinformation," he said. "There are people in Russia whose job it is to try to exploit our systems and other internet systems … so this is an arms race. Example of “AI and power being connected”
  35. 35. • Surveilence – Video • facial recognition • tracking • top of head / shoulders recognition / tracking – drone(s) – USA seriously considering requiring “social media account access” as visa / immigration requirement • E.g. China “citizen number” Risks
  36. 36. Implications from the future prelude to part #2
  37. 37. Theological implications What our culture is being told : why it matters now, not tomorrow. “I am absolutely convinced that the gas chambers of Auschwitz, Treblinka, and Maidanek were ultimately prepared not in some ministry or other in Berlin, but rather at the desks and in the lecture halls of nihilistic scientists and philosophers.” Viktor E Frankl (2012). “The Doctor and the Soul: From Psychotherapy to Logotherapy” Suggests : academic, scientific statements/beliefs about AI made today => effect tomorrow Implies: important to understand and critically examine these statements/beliefs today
  38. 38. https://www.wired.com/2017/04/the-myth-of-a-superhuman-ai/ Excerpt: Many proponents of an explosion of intelligence expect it will produce an explosion of progress. I call this mythical belief “thinkism.” It’s the fallacy that future levels of progress are only hindered by a lack of thinking power, or intelligence. (I might also note that the belief that thinking is the magic super ingredient to a cure-all is held by a lot of guys who like to think.) Theological implications Also interestingly this. But what about the (broken) state of the human heart lust for power love of money devotion to sex Will more available intelligence solve or amplify the issues of the heart ? How do we avoid tainting an AI with these human characteristics nationalism pride fear hatred indifference …
  39. 39. Areas of Implications of AI Economic/social Ethics Use of AI • Significant job loss and structural change • UBI • impact on developing countries • Who owns assets E.g. Uber • Meaning / Purpose without employment Good Bad Intrinsic Risks • legal responsibility for AI • AI goals/value encoding • Biases (e.g. racial) • black box problem • Augmentation • Cure diseases • climate and ecology • solve energy issues • reduce road toll • ease poverty(?) • assisted living • AI assisted research • autonomous weapons • Replacement for “beating heart” • Sex robots • Deep fakes • catastrophic failure • AI arms race • govenment misuse • new security threats • SuperIntelligence Alignment problem / loss of control • investment in AI power not risk mitigation Theological/Philosop hical (Super Intelligence) • create god(s) • become god(s) • alignment issues • justice • freewill • mercy • morality • agency • what does it mean to be human? • mind or matter first • machine rights • charity/empathy/compa ssion • moral to stop it / kill it ? • consciousness • Implications for Christianity
  40. 40. Thoughts on how to respond
  41. 41. General Responses “Today” 1. Recognise the increasing rate of “change” due in part to technology 2. Question how and where AI is being relied upon 3. Start to foster dialogue in workplace 4. Take charge of “tech in our families”
  42. 42. Christian Responses Identify / investigate / raise discussions about resources that Christian faith (should) provide: -  demonstrate the resources that faith in Christ offers such as peace and hope in an uncertain world  basis for human value in a world of less or drastically different and more segregated work  thoughtful discussion of need of “human uniqueness”
  43. 43. Christian Responses  challenge and investigate the cultural assumption that AI/science/tech can solve all of mankind’s problems.  Given the corresponding fears of AGI/SuperIntelligence we have a moment in time in which to do so!

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