Report from UC and Cloud Day 2017 – Social Impacts of Machine Learning and Artificial Intelligence with Tom Morgan (MVP at Modality Systems), Dee Chury (CTO at Dell EMC), and Shawn Harry (Independent Professional Consultant)

These reports are via live reports from Mark Vale.  The full video is available below.

Three65 LIVE From UCDay 2017

If you prefer to read you can continue below.

We are entering the largest, most significant industrial revolution the world has ever seen that will make Steam power seem prehistoric. The advancements in Machine Learning and Artificial Intelligence are rapid and have huge implications on society. Can society keep up with innovation? Is disruption a good thing? What happens to humans when machines automate our jobs? What life will our children have to look forward to and what can we do now to ensure future stability? This is an interesting subject, one that has been floating around since the 1970’s but never more than a pipe dream or science fiction dramatised by motion pictures such as Terminator, Star Trek, Minority Report etc. However, today, it actually looks for the first time a real possibility that we may out create ourselves. Are you prepared for the change? In this session we cover the first industries likely to be affected, what the economy will look like and how we need to start preparing now for our children’s future. Join us for this interesting and often widely contested topic with views from the developer world (Tom Morgan), the new business world (Dee Chury) and general workforce (Shawn Harry).

 

From <https://three65.blog/ucday17/>

 

 

 

Mark Vale is host.

 

M: General discussion on AI.

 

Shawn Harry: All things SfB, UC, MS Stack.

 

Tom: MVP Office Servers and Services.

 

Dee: CTO at Dell EMC consulting.  Talking to customers about workforce transform.  UC part, increasing AI and cognitive computing.

 

M: Long day.  Best sessions?

 

S: Ben’s session, level 200 introduction.  Keynote.

 

T: Background around UC.  Changing.  AI coming in.

 

M: Whole new area of computing, cloud, cognitive services, AI.  Seems good on the face.  What type of impacts.  Is society ready?

 

D: How far do we want to go?

 

T:

 

M: What industries?  Driverless cars in transportation.  10:1 ratio of human driver following convoy.

 

D: Disagree transport first industry.  Regulations even if tech is ready.  Less commonplace.  Public perception, particularly high profile as vehicle.  AI augmenting driver instead of replace.  In general, augmentation instead of replace.  Some jobs completely replaced.

 

M: What does society do with displaced?

T: Still a long way to go.  Cars do a lot of things today.  Not much effort into self-driving training.  Easier to solve.

 

S: Different paradigm.  Easier to enter taxi than public service.  Uber as example.  Autonomous cars already here.  Technical is not problem.

 

D: Challenging to make decisions that impact humans.  Driving down the road.  Do you hit child on side of road versus bus.

 

S: I robot movie gives example.

 

D: Transport is, augmentation instead of full autonomy.  Car can park itself.

 

T: Driverless cars will be quick once worked out because human driver insurance will be more expensive.

 

M: Dedicated lane for autonomous cars.

 

M: Always human cost.  What jobs can taxi drivers look forward to?

 

T: No point owning car.  Changes how to get fuel.

 

S: Reduced to commodity.  To M’s point, how do we and who deals with displaced humans?

D: Universal income.

 

S: Reactive.

 

D: Short term solution.  Necessary.  AI and cognitive computing will make many human based jobs redundant very quickly.  Assume high proportion of jobs.  Technology has been replacing human jobs for 100s of years.  AI introduces pace of change.  How quickly can society adapt.  Concept of universal income will take some of blow away in short term.  Humans are preprogrammed to work.  We won’t want to sit back and take universal income.

 

M: Call an Uber and get in.  Don’t need to go see a GP.  Fill out online.

 

S: Recruiting.  Very little can’t be reduced to an algorithm.  Based on keywords.  How difficult to source, bring back.  Would drive price down.

 

T: Unless you’re creating or manipulating, at risk.  Processing or managing.

 

D: one type is any job involving risk assessment.  Set or rules.  Risk assessor for insurer, nature is go down checklist, score based on probably.  Most susceptible in short term.

 

Legal is another one.  Conversation initial around UC, productivity, billing by the hour.  Speaking with CIOs in law firms, acutely aware business model will change through automation.  Number of people needed decreased.  Competition increase.  Uber type disruptor expected in legal market.

 

T: Comes back to Teams story.  More than collaboration.  Make it easier to get through documents, put in front of people at right team.

 

S: Human experience cannot be reduced to an algorithm.  Humans can interact with facial expressions.  Worked previously for a law firm.

 

D: How you apply.  Easiest way is back office automation.  Going on a for a long time anyway.  Back office automation.  Human interaction more than algorithm.  Based on today agreed.  Had people speak with Watson.  Didn’t realize for a while.  This technology in it’s infancy.  Amazon Echo primitive.  Looking to next year, much more natural conversation.  Measuring how pervasive based on current manifestation is mistake.

 

T: More advanced, vision APIs to analyze faces/emotions.  Interesting things coming

 

M: Are we in danger of letting overrun us if we don’t regulate?

S: What about use case?  HoloLens example at Ford.

 

T: we see companies using.  Need to find right use case.  Can’t just roll out to office to do faster spreadsheets.  Value in manufacturing.  Ford example is good.  Visualize changes.

 

S: VR is incredible from education point of view.  Go back to ancient Rome with headsets on.

 

D: Agree augmented reality will be interesting.  Already see strong use cases.  Walk around property in real estate.  Saves time.  Reduces cost.  Roll AI in.  When watching horror film, know not real.  When AI manipulates.

 

S: AI with Augmented VR is mind-blowing.

 

T: Endless games.

 

M: We can look forward to this because we won’t have jobs.

Anyone who will be displayed.  Human beings need purpose.

 

T: Frees us up to explore new worlds.

 

M: Want SfB or MS Teams, just go to Azure and fill a few questions.  We’ll sit at home with HoloLens, will get bored after 3 months.  Need a purpose.

 

T: We’ll evolve to find those things.  Few people racking and stacking.  Hopeful that spreads out of IT.

 

D: Optimist.  Free up humanity from mundane tasks.  Apply capacity and talents to develop.

 

M: Follow down globalization path to one society?

S: Society becomes commodity.

 

T: Have to be careful with rich societies that break away.

 

D: Technology could be great leveler.  Third world developing countries could have developments accelerated.

 

M: Towns and cities in Africa more developed.  No legacy technologies.  Don’t have cash registers.

 

S: India tried to move to cashless.  Lots of benefits to banking system.  Most banking already cashless.  Not as utopian as put across.

 

D: Reality is in between.  Not a big monolithic how this is going to be.  AI will play role in augmenting instead of replacing.  Truly useful to me would need to do different things than your AI.  I don’t code.  I could develop applications in the future with AI realizing my vision.  Your vision, you enjoy coding.

 

M: As soon as machines are able to code other applications within humans involved gets scary.

 

S: Think that’s science fiction.

 

T: Been on journey of making programming easier.  Next step is to say build me a program that does x, y, z.  Not build me a program that solves world hunger.  Give me a set of data, provide insights.  If I designed a machine to take over the world, still a fundamental challenge.  Technical and non-technical issues.

 

D: Can AI ever truly feel something.  Next generation will be something that can synthetically replicate emotion.  Aware, conscious, as human beings are feelings are governed by our belief systems.  Take a snapshot of what triggers emotion.  Add to algorithm.

 

M: Can’t teach a machine to feel something.  Need to be biological.  Can understand human emotion and how to respond.

 

D: Take that forward and consider types of jobs.  Process oriented.  Could AI generate art?  The inspiration is something would be difficult for a machine to learn.  If was truly conscience, could it be inspired?  A step too far right now.

 

T: Look at two different images, be affected by that.

 

D: To be truly human, <stream becomes distorted>

 

S: in next 10 years, 4 million jobs displaced by robots and AI.

 

M: Opinion this is similar to industrial revolution.  This AI revolution will have more impact.

 

S: 1700s and 1800s Britain was workshop of the world.  Now, Azure has a new feature every couple days.

 

D: AI starts to become a benefit, helps you make sense of increasingly complex world.  Lost hours managing email.

 

M: At the minute AI very experimental.  Just throwing stuff at.

 

T: Being used to deliver commercial benefit.  Companies that use will have unfair advantage.

 

M: When mainstream?

 

S: Already is, Google, Bing.

 

D: Need AI to make sense of all data.  Data warehouse, data lakes.  Too much data for human beings to make sense of.  Will accelerate.  IOT.  Too much for human beings to deal with.  Need AI just to help work out what to do with the data.

 

S: AI or more advanced BI?

 

D:  AI is.  Decision making.  Productivity and communications is part.  Personalized BI.  365.  BI becoming increasingly personalized.  Make decisions quickly.  More confidently.  AI has huge potential.  Augmenting humans instead of replacing.

 

S: Hadn’t thought of augmentation.

 

D: Key is assistance.

 

T: Microsoft service for finding best time to meet.  I need to meet in next 7 days.  Will find.  Bad news for PAs.  Changes game.  Everyone gets a PA.

 

M: All AI in cloud.

 

S: What about rural areas.  US and South Africa.  Far East.  Not well connected to Internet.  Do they get left behind?

 

M:

 

T: Wait for technical enhancements or societal/government funding.

 

M: Different policies on different types of content.  Bandwidth heavy.  ISPs charging for poor service.

 

S: Already here, tiered, net neutrality  Nature of internet.  Commoditized and corporatized.  Don’t know what’s happening under the hood.  Skype, WhatsApp impactful.

 

M: When start to rely on machinery, basic question of whether we even need money.

 

Just a certain amount of credit.

 

D: Replace money with credits is still currency.

 

T: Universal credits.

 

S: Still currency.

 

D: You can monetize information.  Still money.  Potentially in the future, information, in power, influence.  Can’t get rid of money.  Always some kind.

 

T: How do you generate data.  Facebook will buy.  I will buy back some useful tool.

 

M: Take universal income strategy.

 

D: Idea is not you’ll only get this amount.  Basic living amount.  Onslaught of technology displaces.  Cushions blow.  1000 pounds living allowance is enough for basics.  Can survive if cannot work.  Won’t prevent from trying to reinvent and pull in additional income.

 

Should spawn innovation.  Not thinking about how I’ll pay rent/feed myself.  Can afford to take risks.

 

T: Inventors and artists freed up.

 

D: Still contributes to society/culture.  Still benefits even if not monetarily.

 

M: Premise is good.  Every action equal and opposite reaction.

 

S: Science fiction deals with.

 

M: Thank you for your time.  It has been an interesting conversation.

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