SlideShare a Scribd company logo
Jana Eggers
CEO,
@jeggers
Image: http://www.cornerstoneondemand.com/blog/
What to
do when
your next
team
member
is a ‘bot
CC: Geoff Stearns
CC: NASA
CC: anatakti
CC: Geoff Stearns
Artificial light
@naralogics
@jeggers
CC: James Watkins
DID NOT REPLACE THE SUN
@naralogics
@jeggers
BTW...
This little light of mine
@jeggers
@naralogics
Lesson #1:
Algorithms are
introverts
Action #1:
Design the full
expectations and
interactions for your
algorithms,
a.k.a.,
write a job description!
@jeggers
Credit: Stanford University
CC: Terry Freedman
Lesson #2:
The algorithm, the data &
the problem solving
a.k.a., the chicken, the egg &
the bacon
@naralogics
@jeggers
Action#2:Bringhomethebacon
Credit: izquotes.com
Or in other words:
Suppose you went to Ada Lovelace and
asked her the difference between a script
and a program.
She’d probably look at you funny and say,
“Well a script is something you give
an actor, but a program is what
you give the audience.”
That Ada was one sharp lady
Lesson #3: Rocket science is the easy part
@jeggers
Action #4:
Manage the
program,
not just the part
Lesson #4: Beware of Kasparov’s mistake
Action #4:
Expect bugs,
especially in
your data.
BTW, your data
sucks.
@jeggers
Lesson #5: Don’t underestimate the complexity
Action #5:
Bring in expertise for
the algorithm,
the data,
the problem being solved,
the ethics involved.
@jeggers
Credit: /r/AntiAir1018
1. Algorithms are introverts… Build a job description
2. Results are bacon… Focus on results
3. Start small… but carry a big vision
4. Learn from Kasparov… Expect mistakes
5. Shit happens… Bring in expertise @jeggers
@naralogics
@jeggers
Algorithms are
the single greatest instrument
of change
in today’s business world.
Mathematicians
Physicists
Computer Scientists
Data
Compute Power
Neuroscientists
Product Owners
IA & UX
Business Problems
Funding
Ethicists
Social Scientists
Lawyers
Entrepreneurs
Suits
Kids & Grandmas
YouYou You
You
You
You
@jeggers
You
People not like
You
People not like
You
People not like
You
People not like
You
People not like
You
People not like
You
People not like
You
Jana Eggers, What Do We Need to Know About AI?, BoS USA 2016

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Jana Eggers, What Do We Need to Know About AI?, BoS USA 2016

Editor's Notes

  1. Past studies suggest that robots can have a tough time getting people’s attention when they didn’t fully understand the robot’s function or intentions, when they were already busy and when they had nobody else to turn to for social proof, Fischer said. The Stanford group tried to eliminate some of those complications by giving the trash can robot a very straightforward design and testing it in a situation where people would genuinely need its services and might not have much else to do. Mantra… not ghosts in the machine
  2. i.e., you get what you measure Focus on the results
  3. Larry Wall
  4. Definition of insanity
  5. You need to know what problem your are solving first. You’ve got to consider how this could go wrong… think Volkswagen. Recall the early days of computing. Few developers. We have that now too, but it is less clear.
  6. The single greatest instrument of change in today’s business world
  7. Jaron Lanier: “Humans aren’t biological computers”. We need more minds and more ideas in this space. Diversity in thinking is going to help us raise a well-rounded child, and we do need to confront social issues too. What are the social norms? Not to mention ethicists, ethnographers, etc.