Director, DCision Consult Denise Carter's presentation provides an overview of artificial intelligence and looks at how it will affect information professionals
Artificial Intelligence: What is it? Where do information professionals fit?
1. Artificial Intelligence (AI)
What is it?
&
Where do information
professionals fit ?
Denise Carter, DCision Consult | CILIP Conference July 5, 2018
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This is perhaps what
we
imagine
when we
think of
AI …
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… but this is closer to what AI reality
looks like today
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AI needs humans
AI breaks down into data and algorithms
So where do Information Professionals fit
in?
Is it bad news
?
Is it good news
?
Is it a fad ?
AI is here!
6. The UK Government in its Industrial Strategy White Paper,
defines AI as:
“Technologies with the ability to perform tasks
that would otherwise require human
intelligence, such as visual perception, speech
recognition, and language translation”.
The UK House of Lords in their Select Committee Report on Artificial
Intelligence made one addition to this definition:
“AI systems today usually have the capacity to
learn or adapt to new experiences or stimuli”.
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AI and related technologies:
definitions & suggested further
reading
8. The UK:
A
data-driven
economy
The UK government has identified
AI as one of its four grand
challenges.
The Alan Turing Institute has been
named as the UK national research
centre for AI.
The six priority business sectors for
AI are:
① Cybersecurity
② Lifescience
③ Construction
④ Manufacturing
⑤ Energy
⑥ Agricultural technology
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The data lifecycle
is no longer clear and
distinct but interconnected and
interdependent with open networks
of data
Data governance and data
management is becoming
increasingly
complex
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Data capture and processing
is increasingly pervasive
Data collection and use are
becoming harder to separate
Non-sensitive data can
hold sensitive insights
What are the drivers of
complexity?
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Access to metadata
becomes increasingly critical
Data degradation
becomes more of an issue
Knowing which data is poor data becomes
increasingly difficult
And it is becoming more
challenging to know where
data comes
from
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Ethics
Who owns the data?
Who creates the algorithm?
Who can use the data?
Who can buy the data?
Are you dealing with a
human or a robot?
Who owns the algorithm?
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Ethics
ARE INFORMATION PROFESSIONALS
REPRESENTED
IN THESE ORGANISATIONS?
T
H
E
U
The UK Government has committed
£9
million to establishing a Centre for
Data and Ethics
The Nuffield Foundation have pre-
empted this and set up the Ada
Lovelace Institute
A Science & Technology Commons
Select Committee have issued a report
setting out the agenda for the new
Centre for Data and Ethics
There are huge opportunities presented by algorithms to the
public sector and wider society, but also the potential for their
decisions to disproportionately affect certain groups
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Skills
McKinsey Global Institute predict 3skill sets
workers will need by 2030
Higher cognitive skills
Advanced literacy and
writing
Quantitative and statistical
skills
Critical thinking and
decision making
Project management
Complex information
processing and
interpretation
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Skills
Social and emotional skills
Advanced communication and negotiation
skills
Interpersonal skills and empathy
Leadership and managing others Entrepreneurship and
initiative-taking
Adaptability and
continuous learning
Teaching and training
others
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Skills
Technological skills
Basic digital skills
Advanced IT skills and
programming
Advanced data analysis
Mathematical skills
Technological design,
engineering, and
maintenance
Scientific research and
development
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Digital
Literacy
The government industrial
strategy report doesn’t mention
digital or information literacy
skills. They focus on maths and
computer science, particularly
coding as being essential
educational aspirations.
The House of Lords report does
specifically mention the
importance of improving digital
literacy skills.
2018 saw the release of the new
information literacy definition
by CILIP’s Information Literacy Group
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More about AI and the information professional
to be discovered in the Annual Business Information
Survey, which will be published in the September 2018
issue of Business Information Review
Information Professionals are have the right skills
to capitalise on the opportunities AI will offer and
also well-placed to help their own organisations
and society to provide guidance and knowledge
(and wisdom) on data governance, data quality,
information literacy, and ethics
Editor's Notes
10 Powerful Examples Of Artificial Intelligence In Use Today. https://www.forbes.com/forbes/welcome/?toURL=https://www.forbes.com/sites/robertadams/2017/01/10/10-powerful-examples-of-artificial-intelligence-in-use-today/&refURL=&referrer=
HM Government. Industrial Strategy whitepaper. 2017 https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/664563/industrial-strategy-white-paper-web-ready-version.pdf
House of Lords Select Committee Report on Artificial Intelligence. UK: ready, willing and able. April 2018. https://publications.parliament.uk/pa/ld201719/ldselect/ldai/100/100.pdf
Centre for Data and Ethics Call for leader went out in January 2018. Not aware of anyone being appointed as of today.
Department for Digital, Culture, Media and Sport. Rt Hon Matt Hancock
The Science and Technology Committee report acknowledges the huge opportunities presented by algorithms to the public sector and wider society, but also the potential for their decisions to disproportionately affect certain groups.
Read the report summary
Read the report conclusions and recommendations
Read the full report: Algorithms in Decision Making
The report is released as the GDPR becomes effective, and in the wake of the recent controversy centred around the algorithm used by Cambridge Analytica.
Centre for Data Ethics & Innovation
The report calls on the 'Centre for Data Ethics & Innovation' – being set up by the Government – to examine algorithm biases and transparency tools, determine the scope for individuals to be able to challenge the results of all significant algorithmic decisions which affect them (such as mortgages and loans) and where appropriate to seek redress for the impacts of such decisions.
Where algorithms significantly adversely affect the public or their rights, the Committee highlights that a combination of algorithmic explanation and as much transparency as possible is needed.
It also calls for the Government to provide better oversight of private sector algorithms which use public sector datasets, and look at how best to monetise these datasets to improve outcomes across Government.
Chair's comments
Norman Lamb, Chair of the Science and Technology Committee, said:
"Algorithms present the Government with a huge opportunity to improve public services and outcomes, particularly in the NHS. They also provide commercial opportunities to the private sector in industries such as insurance, banking and advertising. But they can also make flawed decisions which may disproportionately affect some people and groups.
The Centre for Data Ethics & Innovation should review the operation of the GDPR, but more immediately learn lessons from the Cambridge Analytica case about the way algorithms are governed when used commercially.
The Government must urgently produce a model that demonstrates how public data can be responsibly used by the private sector, to benefit public services such as the NHS. Only then will we benefit from the enormous value of our health data. Deals are already being struck without the required partnership models we need."
The Committee also recommends that the Government should:
Continue to make public sector datasets available for both 'big data' developers and algorithm developers through new 'data trusts', and make better use of its databases to improve public service delivery
Produce, maintain and publish a list of where algorithms are being used within Central Government, or are planned to be used, to aid transparency, and identify a ministerial champion with oversight of public sector algorithm use.
Commission a review from the Crown Commercial Service which sets out a model for private/public sector involvement in developing algorithms.