Humans, AI and Decisions Making - 2 - Defining and Artificial Intelligence Strategy - Isabel Thompson #SSP2018 8

Defining an
Artificial Intelligence
strategy
IsabelThompson
Senior Strategy Analyst, Holtzbrinck Publishing Group
@IsabelT5000
SSP Annual Meeting, 30 May 2018
ImagecreatedbyMullenLoweforMassArtcampaign

@IsabelT5000
Scholarly Communication
doesn’t have an AI problem

@IsabelT5000
Scholarly Communication
doesn’t have an AI problem
It has a strategy problem

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Problems
• Competing investment priorities

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Problems
• Unclear use cases

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Problems
• Unknown ROI

@IsabelT5000
Problems
• Unknown ROI
• Not enough data

@IsabelT5000
Problems
• Unknown ROI
• Not enough data
• Poor quality or siloed data

@IsabelT5000
Problems
• Unknown ROI
• Not enough data
• Un-agile organizational set-ups

@IsabelT5000
Problems
• Unknown ROI
• Not enough data
• Un-agile organizational set-ups
• A lack of data scientists and tech talent

@IsabelT5000
Outline
1. What is AI?

@IsabelT5000
Outline
1. What is AI?
2. What can it do?

@IsabelT5000
Outline
1. What is AI?
2. What can it do?
3. What should I do?

@IsabelT5000
AI is…
“The field of computer science dedicated to
solving cognitive problems commonly associated
with human intelligence, such as learning,
problem solving, and pattern recognition”
-
Source: https://aws.amazon.com/machine-learning/what-is-ai/

@IsabelT5000
AI is an
intuition
machine

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Submarines don’t swim
https://www.youtube.com/watch?v=K1bfWRgVqMc

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2. What can it do?

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Human-in-the-loop No human-in-the-loop
AdaptiveHard-wired
Adapted from source: https://www.pwc.co.uk/economic-services/assets/ai-uk-report-v2.pdf

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Automation
Manual, repetitive tasks
AdaptiveHard-wired

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Assisted Intelligence
Help perform tasks quicker or better
Automation
AdaptiveHard-wired

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Augmented Intelligence
Augment human intelligence, and
learns from interactions
Automation
AdaptiveHard-wired

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Automation Intelligence
Can adapt and act autonomously
Augmented Intelligence
Augment human intelligence, and
learns from interactions
Automation
AdaptiveHard-wired

@IsabelT5000
Complexity
Theory
Computer
Science
OptimizationEconometricsStatistics
Deep
Learning
Knowledge
Representation
Robotic
Process
Automation
Deep
Question &
Answering
Machine
Translation
Collaborative
Systems
Adaptive
Systems
VisualizationNavigation
Machine
Vision
Audio &
Speech
Natural
Language
Game
Theory
Planning &
Scheduling
Reasoning
Machine
Learning
Sensory
Layer
Behavioural
Layer
Cognitive
Layer
Foundational
Layer
Adapted from source: https://irpaai.com/AI2017-recap-NY/resources/Anand_Rao.pdf

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Classification
Anomaly detection
Clustering
Continuous estimation
Non-industry example
Non-industry example Scholarly Comms example

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Non-industry example
Non-industry example Scholarly Comms example
Recommendations
Ranking
Other optimization
Data generation

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3. What should I do?

@IsabelT5000
Don’t invest in AI!

@IsabelT5000
Don’t invest in AI!
Invest in a business problem

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Use in the core parts of “value chain”

@IsabelT5000
Produce
products more
efficiently
Provide
an enriched,
personalized UX
Promote
right products,
people, & time
Predict
future trends, sales,
R&D
https://www.mckinsey.com/~/media/McKinsey/Industries/Advanced%20Electronics/Our%20Insights/How%20artificial%20intelligence%20can%20deliver%20real%20value%20to%20companies/MGI-Artificial-Intelligence-Discussion-paper.ashx

@IsabelT5000
Produce
products more
efficiently
Provide
an enriched,
personalized UX
Promote
right products,
people, & time
Predict
future trends, sales,
R&D
Editorial
&
Production
Sales,
Marketing,
Discoverability

@IsabelT5000
Top line effects
Bottom line efficiencies

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Top line effects
Bottom line efficiencies
Changing
sources of
“value”

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Competitive advantage

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Competitive advantage
Data

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Partnerships…
Will need to be
more creative
and open

@IsabelT5000
Partnerships…
Will need to be
more creative
and open
Because
most AI talent sits
with vendors

@IsabelT5000
Partnerships…
Will need to be
more creative
and open
Requiring different
relationship
structures
Because
most AI talent sits
with vendors

@IsabelT5000
Buy or build?
How essential
the data is for
competitive
differentiation
How unique your
data set is vs vendors’
Build
Buy
https://www.youtube.com/watch?v=K1bfWRgVqMc

@IsabelT5000
McKinsey’s 5 aspects of a successful AI transformation

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1. Have a business case

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2. Build a data ecosystem

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3. Get the right tools and techniques

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4. Integrate throughout your workflows

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4. Integrate throughout your workflows
5. Adopt an open culture and reskill the workforce

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What if we think of AI as…

@IsabelT5000
What if we think of AI as…
an AI-lien pentopus?

@IsabelT5000
Get the right business case

@IsabelT5000
Build a data ecosystem

@IsabelT5000
Make sure you have the right
tools, people, and techniques

@IsabelT5000
Integrate throughout your workflows

@IsabelT5000
Adopt an open culture and
reskill the workforce

@IsabelT5000
Summary
1. AI can do a lot of stuff

@IsabelT5000
Summary
2. But you need a business case, and AI is not always the answer

@IsabelT5000
Summary
3. We need to think differently about competitive advantage, partnerships & vendors

@IsabelT5000
Summary
4. And change our organizations – structure, people, processes, data

@IsabelT5000
Summary
4. And change our organizations – structure, people, processes, data
5. Because the way businesses and research work is going to look very different

Thank you!
IsabelThompson
isabel.thompson@holtzbrinck.com
@IsabelT5000

Humans, AI and Decisions Making - 2 - Defining and Artificial Intelligence Strategy - Isabel Thompson #SSP2018 8

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