cwin17 san francisco-rob vellinga - interaction between ai and people

HAL 2017 –Interactions between AI and People

CWIN | AIE | SFDecember 7, 2017Rob Vellinga

2© Capgemini 2017. All rights reserved |Hal 2017 – Interactions between AI and People | Rob Vellinga | 12/7/2017

We’re 80 years into the talk aboutand the reality of Artificial Intelligence

Programing to perform Intellectual Tasks

AI Maturity and Popularity

Advances in AI and Machine Learning

Breaking through with AI & Machine Learning

• 1936 – Alan Turing invented the Universal Turing Machine

• 1949 - Claude Shannon wrote ‘Programming a computer for Playing Chess’

• 1950 – Alan Turing invented the Turing Test, to test intelligence in a computer, requiring that a human being should be unable to distinguish the machine from another human being by using the replies to questions put to both.

• 1956 – Allen Newell and Herbert Simon invented the first ‘thinking machine’-Logic Theorist, a punch card calculator, to produce simulation radar maps.

• 1964 - Danny BoBrow (MIT) shows that computers could Process Natural Language

• 1965 – ELIZA, a program that can hold any discourse in English, simulating the conversation of a psychotherapist

• 1968 – A Space Odyssey byStanley Kubrick

• 1980 – First conference of the American Association of Artificial Intelligence is held

• 1986 - First driverless car is designed by Mercedes Benz

• 1997 – NASA successfully completes the Pathfinder Mission with the first autonomous robotic rover to land on Mars

• 1997 – The first official Robocupsoccer match took place. 40 teams of real and ‘simulated’players

• 1997 – IBM’s Deep Blue wins a chess championship against Gary Kasparov, world chess champion

• 2006 - ‘Machine Reading’ (the autonomous understanding of text)

• 2007 – First database of annotated images to aid visual object recognition and facial recognition

• 2009 - Google starts developing Driverless car

• 2014– Amazon announces Alexa Apple’s Siri switches to neural network Machine Learning

• 2017 - Apple builds Core ML a machine learning framework

Scientific Community accepts concept of AI


Why me, why now, why here

People• Anthropometry• Biomechanics• Psychology• Motor Memory• Cognitive Processing• Memory Loading• Patterns• Usability• User-Centered Design

Process• Who are we designing for• What is their mental model• How do they expect the process to

go• How is the process done

manually, supported, augmented, automated

• Define, Design, Develop, Test, Launch

Environments• Places where we spend a lot of time• Places that we spend a lot of effort• Places where we spend a lot of money• Places that are critical to our success• Places that are critical to our safety• Places where the lines between

natural intelligence and artificial intelligence are blurring

Rob Vellinga – Observer, Adopter, Simplify-er


Design Thinking starts with empathy, curiosity and watching the world around us.

“Once a Day, Deeply Observe the Ordinary.Good design thinkers observe. Great design thinkers

observe the ordinary.”

Tim Brown - Ideo


The Reality of my day…..today.Automation, Analytics, User Experience


We’ve been waiting for such a time as this….

AI is not necessarily smarter than a human, but is able to think differently and process LARGE amounts of data.- Kevin Kelley (Wired)

LOW Cost Chips

Cheap computer chips, particularly developed for gaming has resulted in Graphics Processing Units (GPUs)Lowered the cost to explore and enable AI

LIMITLESS Training Sets

Training sets are now able to be created or enable in large, large numbers, thanks to the neural networks.Reduced the time to train and refine, and Increased the scale of deployment of these data sets..

LARGE Scale Neural Networks

Neural networks are now working in large scale.Increased the ability for Deep Learning

1

2

3


Five Skills of AI(AI) is similar to our perception of

human intelligence – this isn’t built ona single element, it’s a combination ofsenses, experiences, and knowledge.

– Christopher Stancombe


Designing for the Now andthe Not Yet

Autonomous vehicles

Computers recognizing images within photographs

Conversational bots

Recommendation engines

NowDrones for personal or corporate security

Predictive maintenance

Diagnose diseases

Personalized advertising

Not yet


The Narrative is that AI is ….

There is no such thing as “an AI.” Enterprises don’t need an “AI.” They need business results in which AI technologies may play a role.

AI is a collection of technologies that can be used in applications, systems and solutions to add specific functional capabilities.

… a product or a thing

“AI” become a generalized marketing term, often with little substance or value.

Very useful, specific functions have been created (speech and image recognition, game playing, fraud and failure prediction), but no general intelligence is in sight, or is singularity (think Hal 9000 or higher).

AI is currently as real as we design it to be.

… pervasive

People define the goals; Technologies execute them.

Technologies (whether AI or not) do not have their own goals that they seek to achieve. Machines execute the programs they have been fed, whether the programs consist of code, data or both. In AI, goal-seeking is an illusion programmed in by people.

Governance and operating parameters define the outcomes that are desired and the guardrails within which the ‘game is played.’

… uncontrollable

AI developers use advanced analytics, special algorithms and large bodies of data to deceive people into believing that their product learns on its own and understands, thinks and empathizes with the user. The tendency is to anthropomorphize technologies. Products, systems, and services with AI are currently as real as we design them to be.

… a simulation and (and replacement) of humanity


Design Spectrum


UnderstandPersonas, Outcomes, Touchpoints, MoT, Context

ObserveEmpathize, Observe, Ask Questions

Define a POVFrame the problem, Define criteria to evaluate,Be more specific than general

IdeateAsk the right questions,What is the ‘wicked’ question,Need volume and variety of ideas

PrototypeUser Scenarios to tell the story,High fidelity to drive real conversations,Define and Design with representative data.

Test Prototype or POCUser Assessments,Usability Testing, Stakeholder Reviews

User-Centered and Outcome-Based

12© Capgemini 2017. All rights reserved |Hal 2017 – Interactions between AI and People | Rob Vellinga | 12/7/2017 12© Capgemini 2017. All rights reserved |

Evolution of AI Design

2D Internet to 3D InternetAugmented reality moves the user experience from a flat screen to an immersive UX in our 3D world.

Outcome-Based DesignsPlay music, Win the game, Set the temperature, Adjust the room, Know my preferences, Optimize the peformance, Self-maintenance

Facial Recognition and UXNow the machine can react to you and adapt rather than you adapting to the machine.

Recent and Ongoing developments that deepen the relationship and trust between AI and People

Michael E. Porter & James E. Heppelmann


Reads facial expressions

Detects emotion

Responds to voice, touch, gestures

Listens....sometimes

Very good at specific tasks

Constantly learning

My AI

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People matter, results count.


Key TakeawaysHal9000 vs. Hal of 2017

Natural Power to Artificial PowerNatural Intelligence to Artificial Intelligence

Outcomes drive AI Design

2D Internet into 3D Internet

cwin17 san francisco-rob vellinga - interaction between ai and people

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