Slides presented at panel debate with AI professionals and attorneys.

1. www.scling.com
AI - legal & ethics
2020-10-09
Lars Albertsson, Scling
1

2. www.scling.com
Machines and decisions
2
Humans
● Infrequent decisions
● New situations
Rules
● Situations that can be
solved by a recipe
Machine learning
● Some classes of problems
(recognition, prediction, games, …)
● Needs lots of examples

3. www.scling.com
Trivial example of learning software
3
If we know a child's age - can
we predict its height?
Expert:
"They seem to grow linearly."
height ~= age * 7 + 51
weights
https://www.mdpi.com/2072-4292/12/10/1667/htm

4. www.scling.com
What could possibly go wrong?
No human to inspect
● Is input sensible?
● Is output sensible?
● Individual adaptations?
● Consistent over time?
● Consistent over input?
4
5 years 86 cm
7 years 100 cm
12 years 100 cm
47 years 379 cm
213 years 1541 cm
-3 years 29 cm
We can handle this.
If we anticipate and prepare.

5. www.scling.com
AI is difficult, really difficult
5https://arxiv.org/abs/1602.04938
https://www.experfy.com/blog/robust-ai-protecting-neural-networks-against-adversarial-attacks/

6. www.scling.com
AI and society
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● Short-term impact from AI is small. Long-term impact is massive.
● Can be explainable
○ Holistic vs step-by-step design
● Can be constrained
○ E.g. disregard ethnicity, gender
● Can be monitored
○ E.g. report conviction / resemblance to training data
● Regulations unavoidable
○ Weapons, face recognition, propaganda
○ Require tech + legal + political collaboration
Tech world cannot be
trusted to handle this alone.
Political / legal world is not
capable of handling this alone.