Dr. Sven J. Körner

sven@thingsTHINKING.net@svenjkoerner

“We humans have a love-hate relationship with our technology. We

love each new advance and we hate how fast our world is changing.”

— Daniel H. Wilson

NO!

We Used the Last ParadigmShift For Good

But We Run The Risk of Becoming the Largest Living Museum of

20th Century Tech.

We’re Missing Out on 21st Century Tech.

Overestimating the Short Term Impact.

Underestimating the Long Term Impact.

AI Isn’t Taking Over

Others Are Overtaking Us With AI.

The First Rule of AI:

Hard Problems Are Easy.

Easy Problems Are Hard.

Substituierbarkeitspotentiale Deutschlandnach Branchen

Quelle: FAZ http://www.faz.net/-gym-9f0y3 / Beschäftigungsstatistik der Bundesagentur für Arbeit, Stand 31.12.2016

Anteil der Beschäftigten mit hohem Substituierbarkeitspotenzial (>70%) an allen Beschäftigten.

Software Engineering vs. AI (SE 2.0)

Problem Code Solution

Problem Solution Code

Context and Proper Training Matter

but use it here...If you train a system on these...

Drawbacks of NN – (Wrong) Training contd

“People remember errorscommitted by AI, but forget human errors”

am am pmpm

ampm

ampm

inout

Input Layer

Output Layer

day shift night shift

am am pmpm

ampm

ampm

1 1 110 0 0 0

inout

Input Layer

Output Layer

day shift night shift

am am pmpm

ampm

ampm

.3 .2 .1.9.8 .9 .6 .4

inout

Input Layer

Output Layer

am pm

ampm

ampm

.3 .2 .1.9.8 .9 .6 .4

(.3+.1)/2 = .2 (.8+.4)/2 = .6

inout

ampm

ampm

Input Layer

Output Layer

am pm

ampm

ampm

.3 .2 .1.9.8 .9 .6 .4

(.3+.1)/2 = .2 (.8+.4)/2 = .6

Gradient Descent

inout

Input Layer

Output Layer

am pm

.3 .1 .1.6.9 .9 .6 .5

(.3+.1)/2 = .2 (.9+.5)/2 = .7

Gradient Descent

inout

Input Layer

Output Layer

ampm

ampm

How Computers and Brains Are Different

How Computers and Brains Are Differentcont‘d

How Computers and Brains Are DifferentPart III

“We found that this information bottleneck measure doesn’t see compression in the same way you or I would. Given the choice, it is just

as happy to lump 'martini glasses' in with ‘Labradors', as it is to lump them in with

'champagne flutes”

Brendan Tracey (SFI, MIT)

Words exist because of meaning. Once you've gotten the meaning, you can forget the words.”

Zhuangzi

“

Common Sense.

For Computers.

What Are Semantics?

Identifying an adult female from other persons might be a data-centric problem

But finding the teacher and the mother requires information not in the data.

adult_female 0.943

adult_female 0.854

mother

teacher

Facebook Bots Invented Their Own Language

Bob: i can i i everything else . . . . . . . . . . . . . .

Alice: balls have zero to me to me to me to me to me to me to me to me to

Bob: you i everything else . . . . . . . . . . . . . .

Alice: balls have a ball to me to me to me to me to me to me to me

Bob: i i can i i i everything else . . . . . . . . . . . . . .

Alice: balls have a ball to me to me to me to me to me to me to me

Bob: i . . . . . . . . . . . . . . . . . . .

Alice: balls have zero to me to me to me to me to me to me to me to me to

Bob: you i i i i i everything else . . . . . . . . . . . . . .

Alice: balls have 0 to me to me to me to me to me to me to me to me to

Bob: you i i i everything else . . . . . . . . . . . . . .

Alice: balls have zero to me to me to me to me to me to me to me to me to

OpenAI GPT-2

Recycling is good for the world, no, you could not be more wrong.

Recycling is NOT good for the world.It is bad for the environment, it is bad for our health,

and it is bad for our economy. I’m not kidding. Recycling is not good for the environment.

It is destructive to the earth and it is a major contributor to global warming. Recycling is bad for our economy.

It increases the cost of a product, and in turn, the price of everything that is made with that product.

Recycling is not good for our nation. We pay a tremendous price for the privilege of having the world’s most

advanced and efficient recycling system. Recycling is a huge, colossal waste of time, energy, money, and resources.

Replacing

DrudgeWork

Human Ability To Learn

Amount of Information

Computer Thinking Speed

???

1st : Automate Expensive Tasks

2nd: Not Just Faster – But More

Your Job

Hertz Car Rental Example

<Type of Clause, Standard, or Paragraph>GDPR Regulation No. 1

<Type of Clause, Standard, or Paragraph>GDPR Regulation No. 2

<Type of Clause, Standard, or Paragraph> Procurement Clause No. 4711

<Type of Clause, Standard, or Paragraph>GDPR Regulation No. 3

<Type of Clause, Standard, or Paragraph>GDPR Regulation No. 5

<Type of Clause, Standard, or Paragraph>NDA Regulation No. 13

<Type of Clause, Standard, or Paragraph>GDPR Regulation No. 4

<Type of Clause, Standard, or Paragraph>NDA Regulation No. 2

<Type of Clause, Standard, or Paragraph>GDPR Regulation No. 6

<Type of Clause, Standard, or Paragraph>Procurement Clause A14

<Type of Clause, Standard, or Paragraph>Export Restrictions Clause

Topics:

• Reference to internal standard of paragraphs/chapters/clauses

• Mapping from clauses to paragraph(s)/chapter(s) in other contracts

• Clause correction and detection• Auto-tagging of contracts• Extract values for further (automated)

processing

Green => Matching OKYellow => Values extractionOrange => Multiple matchesRed => No Gos

AI Lawyer I: Helping to Find Relevant Contract Data and Map

to Existing Clauses, Standards, and Contracts

Semantic Similarity Service

Box.com (Document Management)

Sharepoint (Semantic Compare)

Semantic Clustering (Matrix)

If only 10% are replaced by machines – what would that mean to society?

More than 10% of money for states get lost.Machines don’t pay taxes.Machines don’t consume.

The First Rule of AI:

Hard Problems Are Easy.

Easy Problems Are Hard.

sven@thingsTHINKING.net@svenjkoerner