Presentation by CILIP CEO Nick Poole to the global UN Library, Information and Knowledge Network via their event in Doha, Qatar on the role of librarians and information professionals in leading progress towards more responsible approaches to AI.

1. Leading responsible AI – the role of librarians and
information professionals
Nick Poole
Chief Executive Officer
Chartered Institute of Library and Information Professionals (CILIP)
UN Library and Information Network for Knowledge Sharing, 4th October 2023

2. Contents
• Introduction and overview
• Librarians, information professionals and digital change
• How AI is re-shaping our work as librarians and information practitioners
• Extreme computation and the cost of AI
• Responding to the opportunity for our profession
• A Manifesto for Responsible AI in libraries, information and knowledge

3. Introduction and overview

5. Our role as the UK Library and Information Association
Our impact
We change lives by improving education, literacy and prosperity for all.
We achieve this by raising standards in libraries, information and knowledge management.
Our charitable objects
CILIP’s Charitable objects are to:
“Work for the benefit of the public to promote education and knowledge through the establishment and
development of libraries and information services and to advance information science (being the science
and practice of the collection, collation, evaluation and organised dissemination of information)”.

6. Vision, mission, values
Our Vision
A professional community, dedicated to changing lives and promoting economic wellbeing through
quality information, services and expertise.
Our Mission
To be the leading professional membership association for people working in information, knowledge,
libraries and related sectors.
Our values
• Social justice
• Intellectual freedom
• Evidence-based practice

11. Librarians, information professionals and digital change

12. Our role as librarians and information professionals is not to
problematise new technologies but to engage with them,
understand them and to help improve them in order to maximise
their value to information users.

13. “A heroic librarian looking to
the future with confidence”
DALL-E

14. Hollerith 45-column horizonal electrical sorting machine No. 7407 (circa. 1925), Science Museum Group
We are living and working in an
Information Age, in which entire
industrial economies have woken up to
the fact that the world is made of
information.
We have been seeking to automate the
basic processes of encoding, storing,
retrieving and manipulating information
at scale for more than a Century.
Digital transformation & paradigm-shift
is core business for our profession.

15. https://www.cilip.org.uk/page/digital-leadership-course

17. We must be curious, excited, critical and unafraid.

18. How AI is reshaping our work

19. Not quite exponential, but…
• 37% of organisations have integrated or are integrating AI-augmented decision making in some
form into their systems and processes (up from 10% in 2016)1
• The percentage of enterprises employing AI as part of their technology base grew 270% over the
past four years2
• Businesses estimate that more than 90% of customer interactions, particularly chat/enquiry
handling, will be ‘AI-augmented’ by 20263
• The global AI software market is expected to grow approximately 54% year-on-year and is expected
to reach a forecast size of USD $22.6 billion4
1. Source: Gartner 2021 CIO Survey
2. Source; Gartner 2021 CIO Survey
3. Source: Servion 2018
4. Source: Statista 2022 Worldwide AI Market Growth

21. Search, augmented…
Elicit
Genei
Cradle
Wizdom
RESEARCH SEARCH ENGINES KM DISCOVERY
Bing/
CHatGPT
Google
Bard/
LaMDA
Baidu AI/
ERNIE
Glean
Mem
You
Viable
Andi
Hebbia
Air
Pinecone
Collibra

22. Research, accelerated…

23. https://www.cilip.org.uk/researchreport

24. Our 3 questions
The report The Impact of AI, Machine Learning, Process Automation and
Robotics on the Information Professions set out to address three core
questions:
• What are the ethical implications of our approach to these
technologies – how can we deploy the existing ethical framework for
librarians and ensure that it aligns to emerging work on Data Ethics
and responsible technology?
• How do we ensure that today’s workforce has the skills and
understanding they need in order to enable them to support their
users in participating safely and successfully in a modern world that is
increasingly powered by artificial intelligence (AI), machine learning,
process automation and robotics?
• What should the skillset of the future workforce look like and what is
the curriculum by which we will ensure that the next generation of
information professionals have the skills to keep pace with future
developments in technology?

25. Online & mobile search
Systematic review
Analysis and content mining
Knowledge
Services
Users
Smart spaces
Collections & stock management
Automation of routine processes
New ways to interact with users
New information-seeking behaviours
Algorithmic & data literacy
Ethics
&
values
Keyfindings–impactandapplications

26. AI is disrupting the content lifecycle
Producing
texts
Acquiring
texts into
collections
Categorising
texts
Knowledge
discovery
Curation &
reuse of
texts
Enrichment
of texts
• The first scholarly text composed
entirely by a computer synthesising
existing literature was published by
Springer in 2019
• Publishers are widely using AI to
manage the peer review processes
(Thelwall, 2018)
• There is a close relationship
between the training of Large
Language Models like ChatGPT and
the professional impetus to
embrace open knowledge.

27. Extreme computation and the costs of AI

28. The first wave of generative AI is big, expensive, noisy,
environmentally-costly and prone to make stupid mistakes.
As ethical information professionals, can we lead a 2nd wave
that is smaller, more elegant, more accountable, more
democratic and more sustainable?

29. Extreme computation
AI has moved forward immensely, but
only in one direction – brute-force
computation. In truth, we have made
very little progress towards a
Generalised Artificial Intelligence.
The advances of the past 2-3 years have
been built not on elegance or a deeper
insight into the human mind, but on
data, computation-as-a-service and
connectivity.

30. http://anatomyof.ai

31. “Put simply: each small moment of
convenience – be it answering a question,
turning on a light, or playing a song –
requires a vast planetary network, fuelled
by the extraction of non-renewable
materials, labour, and data.”
Ars Electronica, “Anatomy of AI”

32. Hallucinations
AI ‘hallucinations’ occur where a Large Language Model
perceives patterns in a dataset that are either not there
or are imperceptible to a human observer – and
therefore appear nonsensical.
At its launch, Google’s Bard AI confidently asserted that
the James Webb Telescope had taken the first photograph
of a planet outside our solar system – which was entirely
and provably untrue.
The only solutions to hallucination are (a) to narrow the
field of discourse and (b) to give the AI a human assistant.
The actual first exoplanet photograph, taken in 2004 by Chauvin et al.

33. The Copyright Challenge
An investigation by news website The
Atlantic has identified 191,000
copyrighted books that were used to
train AI models by Meta, Bloomberg
and others.
The development of ever-increasing
Large Language Models creates an
insatiable demand for training datasets –
which is overriding fundamental
copyright laws.
Legislators are struggling to respond at
pace.

34. As ethical librarians and information professionals, we can and
must be concerned about the spiralling societal and
environmental costs of extreme computation and seek to work
with the industry to mitigate them.

35. Responding to the opportunity

36. A student with flawed teachers
This generation of AI operates in one of two main modes:
1. Use a gigantic training dataset (trillions of words) to try and predict the next word in a sentence,
or;
2. Throw everything at solving a problem, and through feedback over many generations gradually
home in on a solution.
But a majority of use cases for today’s Large Language Models treat it like a service, a utility or an
application, not a learning process.
We are not users of ChatGPT – we are its teachers, and we’re not doing a very good job.

37. Our job is not to resist AI, but to help our societies understand
where and how to deploy it, when it is and is not appropriate to
use it and how to regulate its misuse.

38. Generative AI is not a destination we have reached, it is a journey
on which we have only just embarked. The real question isn’t
‘partner or rival’, it’s whether we will help guide that journey in a
positive direction.

39. Differentiating use cases
If we are going to be responsible guides for our users, institutions and societies, we need to
understand and be able to differentiate between the manifold use cases for AI in information search,
retrieval, creation, use, preservation and re-use:
• Using descriptive or discriminative AI to reduce the routine processing of information
• Using AI-based tools to enhance accessibility and support neurodiversity
• Using generative AI as a ‘jumping-off’ point for reports, analysis and synthesis

40. Empowering information users
The widespread promotion of ‘reading’ literacy was one
of humanity’s greatest projects. It empowered
populations, built democracies, accelerated innovation
and the exchange of ideas.
Today, we are all engaged in a new ‘great literacy project’
– to empower entire populations with the complex
literacies (media, information, algorithmic and data
literacy) needed to prosper in a connected world.
www.mila.org.uk

41. I can find reliable
health information to
make decisions to
manage my health and
to care for others.
I can use information
to make a positive
impact in my
community and for
those around me.
I can find trustworthy
information, fact check
it and make sense of it.
I can make the right
decisions for my own
personal and
professional
development and
support those around
me.
I can evaluate, choose
and use the right
online services and
information effectively
and responsibly.

42. Lifelong learning & AI
AI is not on its way, it is already here – embedded
into many of the tools and technologies that our
users are already using to navigate a complex
world of information and data.
We have to mobilise librarians and information
professionals in all sectors – from schools to public
libraries, academic libraries to special libraries – to
support people in developing algorithmic and digital
literacy at every stage of their lives.
Early years
intervention
Primary, Secondary
& FE provision
Higher Education
Post-16 & adult
education
Information in the
workplace
Information skills for
life & citizenship
Lifelong learning &
active ageing

43. New roles and
infrastructures

44. Key findings – future skills
Professional
ethics
Vision &
leadership
Collaboration
User support
Data
stewardship
Procurement
Technical
architecture
The research highlights three key sets of related
findings for the future skills needs of the information
professions:
• The existing ethical basis of the information
professions is well-suited to addressing the ethical
implications of AI, machine learning, process
automation and robotics
• There is a strong alignment between the existing
skillset of information professionals and the
demands of new technologies
• There are some areas in which the information
professions need to be supported to develop new
skills

45. Our professional ethics…
www.cilip.org.uk/ethics

46. Reframing the challenge
The rapid embedding of AI-augmented tools
into our daily lives raises profound legal,
ethical and societal questions.
The question is why people are willing to
surrender life-changing decisions to
algorithms without understanding how they
work or where their information comes from.
“These models are trying to come up with
text that is plausible according to their
model. Something that seems like the kind of
thing that would be written. They're not
necessarily trying to be truthful."
Prof. Vincent Conitzer
Source: Conseil De L’Europe, 2022

47. Our professional skills base
In response to the report into the Impact of
AI, Machine Learning, Automation and
Robotics on the information professions,
CILIP has comprehensively reviewed and
overhauled the Professional Knowledge and
Skills Base:
• Data stewardship
• Algorithmic literacy
• Technology-enhanced KM
www.cilip.org.uk/pksb

48. A Manifesto for Responsible AI

49. Our new-found relevance
Many of the technical and professional skills that our
information users and organisations need from us have
been a part of our skillset for decades, albeit with new-
found relevance, scale and capability.
There is a risk, as there was with the first generation of
search, that the ease-of-use offered by AI leads employers to
see our role as less relevant, not more.
We need to act with pace and urgency to brand our
professional community as the AI-ready professionals of
choice for our employers.

50. A manifesto for positive engagement…
 De-mythologise AI for our users (and ourselves)
 Help to train better AI with Open Data
 Teach our users algorithmic literacy & computational sense
 Teach our AI common sense, norms and morals
 Help guide society toward informed AI regulation
 Help our institutions leverage AI for the good of our users
 Democratise AI and computation as public goods
 Resist the urge to outsource accountability

51. Leading the way…
Our approach to AI today is mostly responsive – seeking to engage with and understand the impact of
tools like ChatGPT, Bard etc.
Can we aspire to be part of the movement to create better AI that is:
• More elegant in its approach
• Less resource-intensive (in terms of computation and environmental & social cost)
• More open and democratic
• Able to display common sense
• More accountable in its outputs

52. I believe that our approach to AI should first and foremost be positive, optimistic and
professional, guided by our ethics and commitment to empowering our users.
We can and must take a lead in defining a benign and beneficial future role for AI in the
lives of the communities we serve.