How AI is Eating the WorldSanjiv R Das

Santa Clara University TiEcon, @Santa Clara

May 5, 2017

Thanks to Arpita Khandelwal for her extensive research in preparing these slides.

Outline

● What is AI?

● Recent applications of AI.

● Why has Deep Learning transformed AI?

● Dangers of AI.

Definition of AIIntelligence exhibited by machines● Artificial Intelligence (AI) /Narrow or Weak AI: “Expert systems that

match or exceed human intelligence in a narrowly defined area, but not in broader areas” e.g. Siri

● Artificial General Intelligence: An artificial neural network that wouldn’t need to be preprogrammed with fixed rules

● Machine Learning (Tom Mitchell): "A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E."

Ability to rewire itself to reflect patterns in the data it absorbed, a mechanism adaptable to its environment, in which advanced skills would emerge organically: “Humans don’t learn to understand language by memorizing dictionaries and grammar books, so why should we possibly expect our computers to do so?”

http://srdas.github.io/MLBook/

Two Types of AI● Rule-Based AI

● Data-driven AI

Example: Checkers

Albert Samuel @IBM began writing code for a checkers game program in 1949. In 1956, the program was demonstrated to the public on live television. In 1962, the computer beat checkers master player Robert Nealey, and IBM’s stocks rose 15 percent overnight.

Rule-based AI can never be more intelligent than its creators, but data-driven AI can!

Usefulness of AIAI in Wearables:

Emotion detectors Could Tell You When The Conversation Is Getting Awkward!

https://www.fastcompany.com/3066867/wearables-that-detect-emotion-could-tell-you-when-the-conversation-is-getting-awkward

Conversational AI

Ford:● Invests in new artificial intelligence software company, Argo AI● Develop the virtual driver system — the brains of their self-driving vehicles● Designed to sense and interpret the world in real-time

Drive.ai: ● Test Vehicle depicts incident-free, unbroken footage shot on a rainy night

Google’s Self-Driving Cars:● The National Highway Transportation and Safety Administration - artificial

intelligence system that controls its self-driving car can be considered a driver under federal law!

AI in Automobiles

Deep Patient:

● An Unsupervised Representation

to Predict the Future of Patients from

the Electronic Health Records

● Discovered patterns hidden in the

hospital data to indicate people’s disposition

to a wide range of ailments, including

cancer of the liverhttps://www.nature.com/articles/srep26094

AI in HealthCare

Image RecognitionThe CIFAR-10 dataset● Consists of 60000 colour images in 10 completely mutually exclusive

classes

● 50000 training images and 10000 test images; 18% test error without data augmentation and 11% with

AI and Gaming

Brains Vs. AI, which began Jan. 11 at Rivers Casino in Pittsburgh, pits Chou and three other leading players — Dong Kim, Jason Les and Daniel McAulay — against Libratus in a 20-day contest in which they will play 120,000 hands of Heads-Up, No-Limit Texas Hold’em poker. All four pros specialize in this two-player, unlimited bid form of Texas Hold’em and are considered among the world’s top players of the game.

Libratus had amassed a lead of $459,154 in chips in the 49,240 hands played by the end of Day Nine.

Positive Reinforcement: ● When machines figure out a way by trial and error and then associate the

positive outcome with the actions that led up to it

● The machine learns without instruction or even explicit examples

● E.g. AlphaGo’s historic Victory against Lee Sedol

AI and Leisure - Gaming

https://www.technologyreview.com/s/603216/5bigpredictionsforartificialintelligencein2017/

Deep Learning

Old Mathematics + New Technology

Artificial Neural Networks + Modern Chip Technology

http://srdas.github.io/DLBook/

Implementing Deep Learning to Detect Breast Cancer

Wisconsin Breast Cancer Dataset

Training the deep learning net

Fitting statistics

60,000 x 784

Validation Metrics (hidden layers 10,10,10)

7510 parameters

Validation Metrics (50,50,50,50,50)

46610 parameters

Validation Metrics (100,100,100)93010 parameters

Predicting stock index direction

● Use all stocks in the S&P500 from 1963 till today

● Fit a deep learning model to 80% of data randomly

● Validate on remaining 20%● 5 hidden layers of 512

neurons each● How accurate is the

prediction of the market direction next day? = 57%

● The statistical significance is a t-stat = 7.54

Latency

Vs

Throughput (#cores)

The Dark Side of AI

The biggest change is going to be seen in the labor markets. Every use of AI is a negative effect on a traditional labor market.

The Atomic Level of Work

David Beyer

The “one second” rule.

What tasks get automated first?

http://www.datasciencecentral.com/profiles/blogs/how-to-put-ai-to-work?xg_source=activity

AI and Humans!

● Algorithmic redlining by deep learning might arrive at the same result but without violating “protected characteristics”

● Broward county (FL) used COMPAS to evaluate re-offense probabilities, but predicted rates were much higher than realized

https://www.theguardian.com/technology/2017/mar/02/robot-tax-job-elimination-livable-wage

Historian Yuval Noah Harari makes a bracing prediction: just as mass industrialization created the working class, the AI revolution will create a new un-working class.

Technology

+

Specialization

The crucial problem is creating new jobs where humans are better than algorithms

AI and JobsThe White House Report (December 2016):

● Millions of lost jobs - the workers earning less than $20 per hour /without a high school diploma most affected

● 9% jobs - completely displaced in the next two decades ● 47% jobs at risk ● To reconcile - expand access to education in technical fields and increase the

scope of unemployment benefits● Calls for further investment in artificial intelligence research and

development - specifically, in cyber defense and fraud detection

“Anything we can do to have more AI will lead to more productivity growth.”

https://www.washingtonpost.com/news/innovations/wp/2016/12/20/ai-could-cost-millions-of-jobs-the-white-house-says-we-need-more-of-it/?utm_t

erm=.8e9c6e3e8073 http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf

AI and JobsFINANCE:

Bridgewater Associates : ● World’s largest hedge fund - project to automate decision-making to save

time and eliminate human emotional volatility● PriOS, the over-arching management software

Goldman Sachs: ● Two out of the 600 equity traders left● Found that four traders can be replaced by one computer engineer● Reducing the number of investment bankers - great cost savings

https://www.theguardian.com/technology/2016/dec/22/bridgewater-associates-ai-artificial-intelligence-management

AI in Hedge Funds

Eurekahedge report : AI hedge fund firms with machine learning outperforming “traditional quants,” and doing so with low correlation

http://www.valuewalk.com/2017/01/ai-hedge-fund-returns/

Last Days of the Stock Picker● BlackRock Inc. announced that it is replacing human stock pickers with machine-run

algorithms for some of its equity funds, signals that the money management industry

is getting the message.

● The world’s largest hedge fund, Bridgewater Associates (US$160 billion in AUM), is

using software to automate its day-to-day decision making.

● The popularity of computerized quantitative trading strategies, and the growing use

of artificial intelligence (AI) techniques, stems in large part from their impressive

returns.

● AI and machine learning hedge funds outperformed both traditional quantitative and

the average global hedge fund, with annualized gains of 10.6 per cent over a two year

period, according to Eurekahege.http://business.financialpost.com/investing/last-days-of-the-stock-picker-as-money-managers-embrace-artificial-intelligence

https://www.linkedin.com/pulse/importance-ethics-governance-artificial-intelligence-marks?trk=v-feed&lipi=urn%3Ali%3Apage%3Ad_flagship3_search_srp_content%3Bz%2FBwgA7F4ss5MPHy8%2FYlkw%3D%3D

WHY THE NEED?

● On one hand potential to do a lot of good ; On the other hand, also being used in ways we don't necessarily notice or understand eg., profiling us for crimes we have yet to commit

● Critical to encourage an interdisciplinary approach to creating regulatory frameworks

Ethics and Governance in AI

Ethical Issues

Unemployment

Robot RightsEvil Genies

Inequality

Artificial Stupidity!

Behavior &

Interaction

Singularity &

Staying in Control

Racist Robots??Security

What’s Being Done?OpenAI :

● founded on the principle that AI should be advanced in a way to benefit humanity, unconstrained by the need to generate financial return.

The Ethics and Governance of Artificial Intelligence Fund:

● An attempt by the Knight Foundation, Reid Hoffman, Pierre Omidyar, the MIT Media Lab amongst others

● Encourage transparent, cross-disciplinary research into how to best manage AI

One Hundred Year Study on Artificial Intelligence (AI100):

● Stanford Study, a long-term investigation of the field of AI and its influences on people, their communities, and society

openai.com

Can Super-powerful AI Eliminate Humans?

● How do we manage uncontrollable AI?

● Encrypted Deep Learning: Build a super-intelligent AI to detect and cure cancer (for example), but encrypt it so that it cannot replicate itself, nor can it be used without human control.

● Encryption prevents it from being stolen by a malevolent player.

● Homomorphic encryption: Only permit a limited range of encrypted predictions. (Allows you to operate/modify information without being able to see it.)

https://iamtrask.github.io/2017/03/17/safe-ai/

Summary● AI is a transformation, not a change.

● Super AI is now possible.

● AI is everywhere, from marketing to medicine and lots more.

● AI will disrupt the labor market, and only some jobs are safe.

● AI has a dark side, from law to lending.

● The second coming of AI is based on Deep Learning.

● AI raises ethical issues.

● AI will need controlling through encryption.

● Artificial General Intelligence (AGI) has arrived! Read more at Stuart Russell’s terrific collection of links:https://people.eecs.berkeley.edu/~russell/research/future/