Insights 2024:

Attitudes toward AI

Insights 2024: Attitudes toward AI

Contents
Foreword		

3

Executive summary

4

Introduction

6

Chapter 1: The current AI landscape9

Awareness of GenAI tools

11

Perceptions of AI

13

AI in practice

15

Chapter 2: A future lens on AI

18

Perceived impact and benefits

20

Perceived drawbacks

23

Expectations

26

Chapter 3: Shaping an AI-driven future

29

Exploring users’ concerns

31

Factors impacting trust in AI tools

33

Actions for an AI-powered future

35

Conclusion		

37

Methodology

38

Appendices39

Acknowledgments

41

Insights 2024: Attitudes toward AI

2

Insights 2024: Attitudes toward AI
Foreword

Advances in science, technology and healthcare shape human progress. Artificial intelligence (AI)has emerged as a formidable force in recent years, helping to reshape how we work, consume
information, innovate and many other aspects of our lives. In particular, recent advances ingenerative AI have the potential to be transformative.
At Elsevier, we bring together trusted content, human expertise and responsibly applied AI
technologies to help researchers, educators and healthcare professionals worldwide advancediscovery, innovation and patient care. In doing so, we continually explore emerging trends andwhat they mean for the communities that we serve. Our reports, including Research Futures,
Clinician of the Future, View from the Top and Confidence in Research, delve into the ever-evolving
landscape of knowledge creation, dissemination, application and medical practice. We are pleased
to share our latest report, Insights 2024: Attitudes toward AI. Based on the insights from nearly 3,000
researchers and clinicians worldwide, this report explores AI’s current state and future prospects.
Their feedback indicates that researchers and clinicians worldwide have an appetite for adopting
AI tools in their work, but not at the cost of ethics, transparency and accuracy. The findings point tohigh quality, verified information, responsible development and transparency being paramount tobuilding trust in AI tools, and alleviating concerns over misinformation and inaccuracy.
Our goal is to provide decision makers with evidence-based insights into how researchers andclinicians feel about AI’s immense potential as well as its challenges. Working together with thecommunities we serve, we strive to shape the future in which AI tools serves all — ethically, fasterand better. We hope you enjoy reading this report and we welcome your feedback.

Sincerely,
Kieran WestEVP Strategy, Elsevier

Insights 2024: Attitudes toward AI

3

Insights 2024: Attitudes toward AI
Executive summary
Generative artificial intelligence (GenAI) has entered themarket at an unprecedented pace, with most researchersand clinicians aware of its biggest applications, following
their emergence in late 2022.

Some main themes emerge from the resultsof the research:➤

Awareness of AI is high, but regular usage is low
generally, with expectations that this will grow.
Institutions have not yet clearly conveyed their AI
usage restrictions, or their preparations for increased
use of AI, to researchers and clinicians.

➤

Attitudes are mixed, but sentiment is more positive
than negative among researchers and clinicians.

➤

Specific actions can help increase trust, and by taking
and communicating them, providers of AI tools canincrease users’ comfort.

What is GenAI?
GenAI, short for generative artificial
intelligence, refers to a category of artificial
intelligence systems and models that havethe ability to generate data, content, or other
outputs that are similar to those created byhumans. These AI systems are designed to
produce new and original content rather thansimply process or analyze existing data.

The artificial intelligence (AI) landscape is changing
rapidly, and in order to ensure the technology has apositive impact on research and healthcare, it’s important
to monitor the views of those who could be using it.
The Insights 2024: Attitudes toward AI research aimed
to do this, by surveying nearly 3,000 people working inresearch (including leaders and corporate researchers)
and in health (clinicians) from around the world.
The research examines the attitudes of researchersand clinicians towards artificial intelligence, including
generative AI, covering its attractiveness, perceived
impact, the benefits to them and wider society, thedegree of transparency to be comfortable using tools that
capitalize on the technology, and the challenges they
see with AI. It also looks at the current usage, and what
respondents think would help them trust AI tools.

Online survey
December 2023 to February 2024

n = 2,999 researchers andclinicians from 123 countries

Insights 2024: Attitudes toward AI

Chapter 1: The current AI landscape
Explore the awareness, perceptions and usage of AI(including GenAI) among researchers and cliniciansaround the world – page 9➤

96% have heard of AI (including GenAI) subsequentstatistics exclude the 4% not familiar with AI➤

54% of those aware of AI have used it; 31% have used
it for work purposes, this is higher in China (39%) thanin the USA (30%) and India (22%)➤

11% are very familiar with AI, i.e. they’ve used it a lot➤

ChatGPT is by far the most well-known AI
product (89%)➤

25% have used ChatGPT for work purposes➤

49% of those who have not used AI cite a lackof time as the reason➤

72% believe AI (including GenAI) will havea transformative or significant impact on theirarea of work

Researchers and clinicians are on a journey fromawareness to usage to benefit when it comes to AI.
Awareness of AI in general is high among both researchersand clinicians, but relatively few say they are currently
very familiar with the technology, having used AI a lot.
Over half of both groups who are aware of AI have used
it, and almost one-third have used it for a specific workrelated purpose; this is highest in China (39%). A lack oftime to investigate such tools is the main reason for notusing AI.

4

Chapter 2: A future lens on AI

Chapter 3: Shaping an AI-driven future

Discover researchers’ and clinicians’ expectations,
including the potential benefits and drawbacks of thetechnology – page 18

Look at researchers’ and clinicians’ concerns in thecontext of building trust and comfort in AI tools,
and read recommendations for developers andinstitutions – page 29➤

95% think AI will help accelerate knowledge discovery➤

94% think AI will help rapidly increase the volumeof scholarly and medical research➤

92% expect to see cost savings for institutions
and businesses➤

67% of those not using AI expect to use it in the next
2-5 years➤

42% of those who have ethical concerns about AI
cite as a top disadvantage that it is unable to replace
human creativity, judgement and/or empathy➤

71% expect generative AI dependent tools’ results bebased on high quality trusted sources only

Researchers and clinicians who are aware of AI recognize
the growing potential of AI tools, and if they’re not alreadyusing them, most expect to do so in the coming two to five
years. Almost all respondents expect AI (including GenAI)
to have an impact by accelerating knowledge discovery
and rapidly increasing the volume of research. While they
identify numerous benefits, respondents also think that
AI will not replace inherently human capabilities likecreativity and empathy. Transparency and quality will be
important in the future as AI use increases.

➤

94% believe AI could be used for misinformation➤

86% are concerned AI will cause critical errors
or mishaps➤

81% think AI will to some extent erode critical thinking
with 82% of doctors expressing concern physicians
will become over reliant on AI to make clinicaldecisions➤

58% say training the model to be factually accurate,
moral, and not harmful (safety) would strongly
increase their trust in that tool➤

Knowing the information the model uses is up to date
was ranked highest by respondents for increasing
their comfort in using an AI tool

Understanding not only their concerns but also the factorsthat build researchers’ and clinicians’ trust in AI tools andtheir comfort using them can help technology developers
create better tools and institutions maximize their benefit.
Almost all respondents are concerned that AI will be
used for misinformation and could cause critical errors
or mishaps. Factual accuracy and up-to-date information
would help increase trust among users.

Recommendations
Based on the survey findings and secondary research,
recommended actions for technology developers andinstitutions – page 35.

For more about the AI views and usage of clinicians,
see the report Insights: Clinician of the Future Attitudes
Toward AI – Key Findings

GenAI technology developers can:https://tinyurl.com/ai-cotf➤

Enhance accuracy and reliability➤

Increase transparency➤

Strengthen safety and security

Institutions employing researchers and clinicians can:For more on AI usage and perceptions among researchers,
see the report Insights: Researchers Attitudes to AI –Key Findings.
https://tinyurl.com/ai-researchers➤

Establish policies and plans and communicate
them clearly➤

Build governance and expertise

https://tinyurl.com/ai-attitudes➤

Provide training and capacity➤

Ensure accessFollow Elsevier Connect on
X (formerly Twitter), Facebook and LinkedIn

Insights 2024: Attitudes toward AI

5

Insights 2024: Attitudes toward AI
Introduction“The development of AI is as fundamental as thecreation of the microprocessor, the personal computer,the Internet, and the mobile phone. It will change theway people work, learn, travel, get health care, andcommunicate with each other.”Bill Gates 2

Generative artificial intelligence (GenAI) has entered
the market at an unprecedented pace, with the majorityof researchers and clinicians aware of its biggest
applications, including ChatGPT, within a shortperiod of launch.

What is GenAI?
GenAI, short for generative artificial
intelligence, refers to a category of artificial
intelligence systems and models that havethe ability to generate data, content, or other
outputs that are similar to those created byhumans. These AI systems are designed to
produce new and original content rather thansimply process or analyze existing data.1

ChatGPT, Open.ai’s generative AI platform, reached 100
million users within two months of its launch in November
2022, making it the fastest growing consumer application
ever at the time.3
Artificial Intelligence (AI) had been prevalent in our lives
for many years before GenAI, helping us search, buy andnavigate, among many other things. But the developmentof GenAI is boosting the impact of the technology overall:estimates suggest it will generate trillions of dollars every
year.4 This is reflected in the acceleration of investment in
GenAI, leaping from $4.3 billion in 2022 to $22.4 bn
in 2023.5

The future of GenAI
The expectation is that the return on investment will beworthwhile. According to consulting firm EY, investment
in AI could add 1% to global GDP by 2033 – the equivalentof $1 tn.6 EY expects the US to lead this investment, though
they note that China and Europe are not far behind.
Even more optimistically, the McKinsey Global Instituteestimates GenAI will add $4.4 tn in value to the global
economy annually.4 Goldman Sachs goes even further,predicting an increase of 7% in global GDP – almost $7 tn.7
Where are these benefits coming from? GenAI istransforming the very nature of work – and it’s happening
much faster than we thought. McKinsey projects AI willautomate half of today’s work activities between 2040
and 2060, more than a decade earlier than previous
estimates, thanks to acceleration of the technology’s
development and usage. The results from our survey also
indicate that the impact of AI on research and healthcare
will be transformative over the next few years.

Likely impact on researchand healthcare
McKinsey indicates that of the four areas likely to accountfor three-quarters of the added value of GenAI is researchand development, where GenAI could “deliver productivity
with a value ranging from 10 to 15 percent of overall R&D
costs.”4 This is notable in the pharmaceuticals and medical
products industry, where GenAI is expected to have arelatively high impact in terms of R&D productivity. In
comparison, they think healthcare is likely to see a greater
impact in supply chain and logistics productivity.
As noted in Elsevier’s Clinician of the Future Report 2023,
AI has gained attention in healthcare for its potential
to automate certain tasks, such as filling in forms orsummarizing notes, thereby increasing efficiency andsaving clinicians’ time.8
But the potential of AI goes far beyond boostingproductivity. An MIT Technology Review Insights report
describes health and medicine as “a productive testing
ground for AI,” with applications including tracking
disease spread and supporting drug discovery, as wellas summarizing medical notes and even communicatingwith patients.9

Insights 2024: Attitudes toward AI

6

There are just as many opportunities for AI in research.
As Bill Gates noted on his blog Gates Notes, “AIswill dramatically accelerate the rate of medical
breakthroughs.”2 In particular, he mentions the large
amount of biological data resulting from complex
systems, which AI applications are already helping
researchers untangle and understand.
AI is already being used in clinical trials. Given thatpharma companies spend about 20% of their revenue on
research and development, the McKinsey Global Instituteestimates that GenAI could contribute $60 bn to $110 bn
a year to the industry.4 Specifically, applications include
identifying lead molecules, where GenAI could cut down
research time from months to weeks. GenAI also has
a role to play in identifying findings during clinical trials,
especially with the increase in digital technologies usedin clinical research.

Companies are embracing GenAI
Organizations around the world are already embracing
new AI-powered technologies to improve efficiency andboost innovation. A 2022 MIT Technology Review Insights
report showed that 94% of organizations were using AI,
though only 14% aimed to achieve “enterprise-wise” AI
by 2025.9 Developments since this report clearly show thepotential application of AI, GenAI is changing the picture
rapidly across every function, including the more creative
tasks previously considered inherently human.
“I can’t think of anything that’s been more powerfulsince the desktop computer.”Michael Carbin, Associate Professor, MIT,and Founding Advisor, MosaicML9

Indeed, in a global EY survey of corporate CEOs, 62%
acknowledged the urgency of acting on GenAI, in this caseto prevent their competitors from “gaining a strategicedge.”6 But the survey also uncovered a dilemma: 61%of business leaders shared reservations around GenAI
because of “the uncertainties surrounding the formulationand execution of an AI strategy.”
Before organizations can benefit from the potential of
GenAI, these reservations, and risks such as bias andprivacy that are inherent in the technology, will need tobe addressed. According to EY, organizations will need toinvest in infrastructure as well as technology and skills intheir workforce.6 Almost 70% of respondents to an MIT
Technology Review Insights survey said a unified data
platform for analytics and AI is crucial. This includes ‘data
lakehouses’ – a hybrid of data lakes, where data is stored
in its original form, and data warehouses, systems foranalyzing and reporting data from multiple sources. 10
Insights 2024: Attitudes toward AI

Getting the workforce on board
In order to unlock its full potential, it’s not just thecompanies and institutions that will need to be on board,but also the people who will be using it. As noted by MIT
Technology Review Insights, “Risk aversion and cultural
factors, like fear of failure, also need to be addressed todrive AI adoption in the workforce.”
Unlike the kind of automation that has changed theway we work in the past, for example with the adventof machinery to take on manual tasks, emergent GenAI
technology will likely have the biggest impact onknowledge work, tasks involving creativity, collaborationand decision making.
According to McKinsey, GenAI has only shifted thepotential to automate physical work by 0.5%.11
In comparison, the potential to technically automate
the application of expertise increased from 24.5% in 2017
to 58.5% in 2023, thanks to GenAI.
The report also suggests that GenAI is likely to havea major impact on STEM professionals: the estimatedtechnical automation potential of activities performed bythis group was 28% in 2017; with GenAI, this doubled to
57% in 2023. Numbers are similar by education level, withGenAI doubling the automation potential for those in roles
with a master’s, PhD or higher.4
Today’s STEM professionals are already using AI or are
expecting to use it. Elsevier’s Research Futures 2.0 report
released in early 2022 showed that 8% of researchers werealready using AI extensively in their research, principallyto help with analysis and processing large data sets.12
In the Clinician of the Future Report 2022, over half (56%)
of clinicians surveyed expected to be making most of theirdecisions using clinical decision support tools that use AI
in 10 years’ time.13“Clinical information is only one element of theclinical decision-making process, from assessment
to diagnosis and treatment. Heuristic knowledge
drives decision making, and this can be supported
by artificial intelligence (AI) and machine learning
prediction models.”Clinician of the Future Report 2022

7

Concern about GenAI
The picture is not simple, though: clinicians and thegeneral public report being excited but also concerned
about GenAI.15 In Clinician of the Future 2023, a sizable
minority, 28%, of clinicians said they find it undesirable
for AI to be used in clinical decision-making tools
in the future.16
There are several commonly reported concerns among
various groups, primarily including accuracy and therisk of misinformation, bias, privacy and security, andto a lesser extent, ethical issues.15 Many of theseconcerns are not unique to GenAI, but the technology
is amplifying them.

Understanding researchers’
and clinicians’ views
The GenAI landscape is changing rapidly, and in order toensure the technology has a positive impact on researchand healthcare, it’s important to monitor the views of
those in these areas.
The Insights 2024: Attitudes toward AI research aimed
to do this, by surveying nearly 3,000 people working inresearch (including leaders and corporate researchers)
and in health (clinicians) from around the world.
The research examines the attitudes of researchers andclinicians towards artificial intelligence (AI), including
generative AI (GenAI), including its attractiveness,
perceived impact, the benefits to them and wider society,the degree of transparency required around AI to be
comfortable using tools that capitalize on the technology,
and the challenges they see with AI. It also looks at thecurrent usage, and what respondents think would help
them trust AI tools.

Insights 2024: Attitudes toward AI

Insights 2024:
Attitudes toward AI

When:
What:
Who:

December 2023 to February 2024
15-minute online quantitative survey
2,999 respondents from across
123 countries- 2,284 researchers- 1,007 clinicians(of whom 292 are also included as researchers)

Results: To improve representativeness weweighted responses by region, andto equally represent researchers andclinicians in totals. Clinicians areweighted equally by doctors and nurses.
See appendices for more detail on methodology
and sample.

You can explore these themes across three chaptersin this report:➤

Chapter 1: The current AI landscape
Explore the awareness, perceptions and usage of AI(including GenAI) among researchers and cliniciansaround the world.

➤

Chapter 2: A future lens on AI
Discover researchers’ and clinicians’ expectations,
including the potential benefits and drawbacks of thetechnology.

➤

Chapter 3: Shaping an AI-driven future
Look at researchers’ and clinicians’ concerns in thecontext of building trust and comfort in AI (including
GenAI) tools, and read recommendations fordevelopers and institutions.

8

Insights 2024: Attitudes toward AI

The current AI landscape

Chapter 1

The current AI landscape“AI is here, and it works. We need to think how
to use it properly.”
Survey respondent, researcher, Kazakhstan➤

96% have heard of AI (including GenAI) – subsequentstatistics exclude the 4% not familiar with AI➤

54% have used AI (including GenAI) and 31% have used
it for work purposes; this is higher in China (39%) than in
the USA (30%) and India (22%)➤

11% are very familiar with AI (including GenAI),i.e. they’ve used it a lot➤

ChatGPT is by far the most well-known AI product (89%)➤

25% have used ChatGPT for work purposes➤

49% of those who have not used AI cite a lack of timeas the reason➤

72% believe AI (including GenAI) will havea transformative or significant impact on theirarea of work

Researchers and clinicians are on a journey from awarenessto usage to benefit when it comes to AI. Awareness of AI ingeneral is high among both researchers and clinicians, but
relatively few say they are currently very familiar with thetechnology, having used AI a lot. Over half of both groups
who are aware of AI have used it, and almost one-third haveused it for a specific work-related purpose; this is highest in
China (39%). A lack of time to investigate such tools is themain reason for not using AI.

Familiarity
with AI
Very familiar(used it a lot)

Futureusage of AI

Not familiar

4%

Not used

11%

Don’t expect toor not sure

46%

96%
Familiar

85%
Somewhat / a little familiar

Fig 1.

Present
usage of AI

33%

54%

31%

Have used
for work

Have used
23%
Have used for non-work

67%
Expectto use67%
Expect to use

Question: To what extent are you familiar with AI (including GenAI)? n=3,118
Question: Have you used an AI (including GenAI) product or an AI feature on a product you use regularly? n=2,999
Question: Do you expect you will choose to use AI (including GenAI) in the near future? n=1,330

Insights 2024: Attitudes toward AI

10

Awareness of GenAI tools
Given the rapid rise of GenAI tools, particularly ChatGPT,
it is perhaps unsurprising that most people are at least
aware of its existence. Global Counsel surveys show thatabout 90% of people in the UK, US and Germany haveheard of GenAI.17 Similarly, a 2023 survey by Pew ResearchCenter showed that 90% of Americans say they “haveheard at least a little about artificial intelligence.” 18
However, drilling down reveals only about one-third
have heard a lot about it.
The current survey reflects these findings: almost all(96%) have heard of AI. Awareness is highest in China
at 99% (see accompanying databook for full details).
Globally, only 11% are very familiar with AI, having used ita lot, this is higher among researchers (14%) than
it is clinicians (8%).

Demographics seem to have an impact when it comesto familiarity with AI. We see that in APAC those very
familiar and using AI a lot is highest 13%, compared to 8%
in Europe (see accompanying databook for full details).
Please note: all subsequent statistics in this report exclude
the 4% not familiar with AI.

ChatGPT is the most familiar GenAI tool
ChatGPT is by far the most well-known AI product, with
89% of survey respondents globally being familiar with it.
Researchers (94%) are more likely than clinicians (84%) tohave heard of it.

Levels of familiarity with AI (including GenAI)% Total(n=3,118)
Not at all familiar(never heard of it)% Researchers(n=2,355)

4

53

A little familiar

39

Somewhat familiar
11

Total familiar

96%

RE

44

35
46

Very familiar(used it a lot)

Significantly higher or lower than total% Clinicians(n=1,060)

48
14
97%

RE

44

CL

CL

8

CL

95%

Significantly higher than Role/ Region/ Country (indicated by first two letters e.g. AP = APAC)
Asia Pacific = AP
Europe = EUMid. East & Africa = MEA

North America = NA
South America = SA

China = CH
UK = UK
USA = US

RE = Researchers
CL = CliniciansFig 2. Question: To what extent are you familiar with AI (including GenAI)?

Insights 2024: Attitudes toward AI

11

AI products familiarity and usage
AI Product

ChatGPT

Bard (Google)

Bing Chat

Gemini (Google)

MS Copilot (in Word, Excel, PPT)% Heard of it89%

RE: 94%25%

CL: 84%40%

RE: 42%

6%

CL: 38%39%

RE: 44%

7%

CL: 33%

22%

RE: 26%2%

CL: 17%22%

RE: 24%

ChatPDF.ai

OpenEvidence

17%

RE: 17%2%

CL: N/A

13%

RE: 17%2%

CL: 10%8%

RE: 6%

1%

CL: 9%

Significantly higher or lower than total

31% Researchers
CLCL

19% Clinicians
CL

CL

RE

Significantly higher than Role/ Region/ Country (indicated by first two letters e.g. AP = APAC)
Asia Pacific = AP
Europe = EU

Fig 3.

CL

CL: 19%4%

Semantic Scholar% Used it for work

Mid. East & Africa = MEA
North America = NA

South America = SA
China = CH

UK = UK
USA = US

RE = Researchers
CL = Clinicians

Question: Which of these AI products, if any, have you heard of before today? n=2,999
Question: Which, if any, AI products or AI features have you used for work purposes? Shown to only those aware of tool base variable
n=81 to 2,713: % shown is proportion of 2,999.

This reflects the rapidly increasing awareness and useof ChatGPT. In March 2023, just under a year before
the current survey, Pew Research found that 58% of US
adults had heard of ChatGPT.19 In a consumer survey
by Capgemini Research Institute the same year, 51% of
respondents were aware of the latest trends in GenAI and
had explored tools like ChatGPT and DALL-E.20 A further
35% were aware but had not yet tried the tools.
In the current survey, we found that across mostgeographical regions, ChatGPT was the most well-known
tool. Familiarity was high across all regions but notably
lower in South America at 75% (see accompanying
databook for full details).
The next most familiar GenAI tool is Bard (40% overall),followed by Bing Chat (39%), Gemini (22%) and MS Copilot(22%). Lesser-known tools are Semantic Scholar (17%),
ChatPDF.ai (13%) and OpenEvidence (8%). In most cases,
researchers are more likely than clinicians to be familiar
with the tools.

Insights 2024: Attitudes toward AI

The most well-known GenAI tools
we asked participants about
ChatGPT – a chatbot developed by OpenAI
Gemini – formerly known as Bard, a chatbot developedby Google
Copilot – formerly Bing Chat, an AI-powered feature
by Microsoft, built into the browser, and Microsoft 365
Copilot, built into Microsoft 365 apps including Word,
Excel, PowerPoint, Outlook and Teams
Semantic Scholar – an AI-powered research tool forscientific literature, developed at the Allen Institutefor AIChatPDF.ai – AI-powered text recognition, table
extraction and data analysis for PDFs
OpenEvidence – an AI system to aggregate, synthesize
and visualize clinically relevant evidence

12Perceptions of AI
While awareness of certain GenAI tools is high among
both researchers and clinicians, attitudes to thetechnology are more variable, with 49% of respondents
globally saying they feel mixed about AI, able to see bothpotential and drawbacks.
“All emerging technologies, including AI, have bothadvantages and disadvantages. It is essential to further
develop and regulate these technologies, aiming to
extract maximum benefits.”
Survey respondent, researcher, Canada

However, sentiment is generally more positive about the
impact of AI than negative: 36% of respondents say AI isa welcome advancement, compared to just 1% who see
mostly drawbacks. Researchers (41%) are more positive
about the technology than clinicians are (32%). Clinicians
are also more unsure, with 17% saying they need to see
how AI develops, compared to 10% of researchers.
“Although there would be many benefits, it would also
wreak havoc if false information is spread.”
Survey respondent, nurse, Mexico

A report by Stanford University highlighted majordifferences in sentiment about AI, with that of people in
Asia more positive than those in the West.21 In this survey,
we see that those in North America are more skeptical,
28% are positive about AI, this compares to 40% in APAC
and 46% in China (see accompanying databook for fulldetails). A similar pattern is evident in Pew ResearchCenter Survey in the US, 52% of adults reported being
more concerned than excited about the use of AI in daily
life.18 Previous research conducted by the UK’s Office for
National Statistics also reveals a mixed picture when it
comes to perceptions.22 In a 2023 survey of adults, 28%
said they think “AI brings greater risks than benefits,”
compared to just 14% thinking the opposite.
Men have also been shown to be more positive than
women about AI, and this is corroborated in the current
survey; men are much likely to be positive about the
impact of AI (45%) than women (27%) (see detailed
findings in databook).
There is little evidence of differences in sentiment by age
group, however, there may be differences by sector androle. In a survey by Gapgemini, executives have a morepositive outlook: 74% “believe the benefits that generative
AI brings outweigh the associated risks,” rising to 80% of
executives in pharma and healthcare companies.23

Overall feelings towards AI (including GenAI)% Total(n=2,999)
Positive – it’s a welcome advancement% Researchers(n=2,264)36

Mixed - I can see both potential and drawbacks

Negative – I see mostly drawbacks
Significantly higher or lower than total

41
49

Unsure – I need to see how this develops% Clinicians(n=1,007)
32

CL

50

48

13

17

10

1

RE

1

1

Significantly higher than Role/ Region/ Country (indicated by first two letters e.g. AP = APAC)
Asia Pacific = AP
Europe = EUMid. East & Africa = MEA

North America = NA
South America = SA

China = CH
UK = UK
USA = US

RE = Researchers
CL = CliniciansFig 4. Question: What are your overall feelings about the impact of AI on your area of work?

Insights 2024: Attitudes toward AI

13

widen knowledge workers’ roles. And 60% say GenAI willcompletely revolutionize the way they work.

AI will have a major impact
The vast majority (95%) of respondents who are aware of
AI believe it will have an impact on their work (1% think
it won’t, 4% don’t know), with 72% believing the level ofimpact will be either transformative or significant. There issome variation in the expected extent of that impact, witha higher proportion of researchers (28%) than clinicians(22%) expecting the impact to be transformative.
These results are echoed in other research. In View fromthe Top: Academic Leaders’ and Funders’ Insights on the
Challenges Ahead, AI was identified as “a transformative
force that will affect all aspects of university functions,from teaching and research to administration,” with some
respondents expecting AI to have a “profound impact”
across disciplines.24
Capgemini research also reveals the sentiment that GenAI
could transform work.23 In their survey, 70% of consumers
said they believe GenAI will make them more efficient atwork and free up time to be more strategic, while 70%
of executives agree GenAI will allow organizations toLike much of the other research, the Network ReadinessIndex (NRI), which looks at countries’ digital readiness,
highlighted a mixed perception of GenAI among the
public.25 The NRI shows a geographical split, which shows
the USA ranks highest in terms of digital readiness, largely
due to their pioneering position in technology, followed by
Switzerland and Hong Kong.25 However, it’s the Republicof Korea, Israel and Japan that lead the ‘people’ pillar of
digital readiness, which comprises individuals, businesses
and governments.
The current study somewhat reflects this distribution
with more in APAC believing the impact of AI will betransformative or significant (76%) versus North America(66%) and Europe (65%) (see accompanying databook
for full details). This regional pattern was also evident
in Clinician of the Future 2023, in which cliniciansin China were least likely to find the future use of AI
undesirable (17%), compared to 33% in Europe and 31%
in North America.26

Expected level of impact of AI in area of work
% Total(n=2,999)
Transformative(i.e. it will make a marked change)% Researchers(n=2,284)
25

Significant(i.e. a notable change)3

None(i.e. no change at all)1

Don’t know/not sureSum of Transformative + Significant(excluding Don’t know / not sure answers)

45
24

21
3

4

1

0
4

3

72%

74%

RE

5
CL

RE

71%

Significantly higher than Role/ Region/ Country (indicated by first two letters e.g. AP = APAC)
Asia Pacific = AP
Europe = EU

Fig 5.

22

CL

44

23

Low
(i.e. a small change)

Significantly higher or lower than total

28
44

Some
(i.e. a partial change)% Clinicians(n=1,007)Mid. East & Africa = MEA
North America = NA

South America = SA
China = CH

UK = UK
USA = US

RE = Researchers
CL = Clinicians

Question: What do you think will be the level of impact of AI (including GenAI) in your area of work in the near future?

Men and women differ in AI views
Men are significantly more likely than women to feelpositive about AI, at 45% and 27% respectively. Womenare more likely than men to feel mixed (54% versus
44%) and unsure (17% versus 10%).
This difference is reflected in their expectations:men are more likely than women to think AI will betransformative, at 29% and 21% respectively. Overall,more women (26%) than men (20%) expect the change
resulting from AI to be only partial.
Insights 2024: Attitudes toward AI

Conversely, women are more concerned about the
ethical implications of AI on their area of work, with
30% of women reporting significant concerns,
compared to 24% of men.
Women also appear to be more aware of their
institutions’ actions related to AI, with women lesslikely than men to be unsure how their institution
is preparing for AI usage, and more women thanmen likely to be aware of new AI leadership at their
institutions.
14AI in practiceOf those familiar with AI, more than half (54%) of
respondents in the current research have actively used AI,
with researchers (59%) more likely than clinicians (50%)
to have used it.

respondents shared that 11% of their clinicaldecisions were assisted by GenAI, with nurses(16% of clinical decision) using it more than doctors(7% of clinical decisions).

Proportionally more researchers (37%) than clinicians(26%) have used AI tools for a work-related purpose.

When we look at the results at a more granular level,
regional differences emerge, APAC is more likely to haveused AI for work related purposes (34%) versus North
America (30%), and it is notably higher in China (39%).
There are difference by years of experience in work andgender too. Those active 6-10 years have used AI for awork-related purpose most, while those most experienced
are less likely to have used AI than average, while men(35%) are more likely than women 27% to have used
AI for work purposes (see detailed findings
in databook).

While this survey is setting a baseline, there areindications of an upward trend. In the Research Futures
2.0 report published in 2022, 8% of respondents reported
using AI extensively in their research.27 The researchers
who used AI reported using it to analyze research results(66%), process large data sets to spot defects (49%),
help conduct research (36%), enhance images (26%) andgenerate hypotheses (17%).
Elsevier’s Clinician of the Future 2023 report noted thatAI technology is already helping clinicians learn andmake decisions – not displacing or replacing them, but
supplementing and supporting them.3 Clinicians surveyed
were open to the potential of AI to improve patientcare, though in practice this was limited at the time:

Elsevier’s Research Futures 2.0 report in 2022 revealed
simlar differences in the extensive use of AI in research.

Usage of AI and context for usage% Total(n=2,999)
Yes – for a specific work-related purpose% Researchers(n=2,284)
31

Yes – but just to test it or fora non-work purpose

37

23

No

Significantly higher or lower than total

26

CL

24

22
44

Don’t know / not sure

% Clinicians(n=1,007)

49

40

1

RE

1

1

Significantly higher than Role/ Region/ Country (indicated by first two letters e.g. AP = APAC)
Asia Pacific = AP
Europe = EUMid. East & Africa = MEA

North America = NA
South America = SA

China = CH
UK = UK
USA = US

RE = Researchers
L = CliniciansFig 6. Question: Have you used an AI (including generative AI) product or an AI feature on a product you use regularly?

Years’ experience and perceptions of AI
Years of experience in work have an impact on people’s
perception of AI and knowledge of their institutions’AI-related actions. As years active in their area of work
increases, so too does the proportion who feel unsure
about AI. Those newest to their roles tend to be morepositive about AI, and they believe it will free up time

Insights 2024: Attitudes toward AI

for higher value work and increase work consistency(see detailed findings in databook). Those with over 35
years’ experience in their area of work are least likely tothink AI will be transformative, at 19%, and most likely
to expect only a partial change, at 28%. This group isalso more likely to be unsure how their institution ispreparing for AI usage.

15

In terms of tools being used, it is not surprising given its
high awareness levels that ChatGPT is the AI tool usedmost for work (see figure 3). Specifically, one-quarter (25%)
of respondents in the current study have used ChatGPT for
work, with usage significantly higher among researchers
than clinicians (31% vs 19% respectively). Comparatively
few (4%) report using MS Copilot(in Word, Excel and PowerPoint).

Reasons for not using AI products or AI features% Total(n=1,330)% Clinicians(n=505)% Researchers(n=944)

I haven’t had time to investigate/experimentwith such tools

49

52

I don’t yet have a subscription/ login
to such tools

26

24

I haven’t found a tool yet that meets my needs

25

28

CL

I have concerns about such tools (e.g. the risks
have not yet been adequately mitigated)

22

25

CL

I don’t know of any such tools

16

14

There are restrictions on my use of such tools(from my organisation, funder, publisher etc.)

12

14

Don’t know / not sure

4

3

Other
(please specify)

2

3

Significantly higher or lower than total

28
23
19
19
10

CL

5
CL

RE

RE

1

Significantly higher than Role/ Region/ Country (indicated by first two letters e.g. AP = APAC)
Asia Pacific = AP
Europe = EUMid. East & Africa = MEA

Fig 7.

47

CL

North America = NA
South America = SA

China = CH
UK = UK
USA = US

RE = Researchers
CL = Clinicians

Question: Which of the following describes why you haven’t used an AI product or AI feature?

Why not use AI?
The most common reason for researchers and clinicians
not having used AI is lacking the time to investigate orexperiment with the tools – 49% of respondents globally
cite this as the reason, including 52% of researchers and
47% of clinicians.
Other reasons given for not having used AI tools include
lack of access (26%), not having the right tools (25%) andhaving concerns about AI tools (22%).

Insights 2024: Attitudes toward AI

More than one in ten (12%) overall say they haven’t used
AI due to restrictions, for example, from their employer,
funder or publisher.
There are some differences by region: we see that more
respondents in South America have not used AI tools
due to a lack of subscriptions to such tools (29% vs 20%
in North America) and restrictions are highest in North
America (15%) which is higher than Europe (9%)(see detailed findings in databook).

16

Although only 2% of respondents are prohibited fromusing AI in any way (see figure 8), 27% report being
prohibited from uploading confidential information to
public GenAI platforms, 18% are prohibited from using it
for certain purposes and 10% are prohibited from using
certain tools. More than one-quarter (26%) say they areprohibited from using AI tools due to lack of budget topay for them. A lack of budget is the most commonly citedrestriction, at 35% in South America and Middle East andAfrica. One-third (33%) of respondents are unaware of
restrictions on AI usage at their institution.

Many respondents are also unaware of their institutions’plans when it comes to AI, with 44% of respondents notknowing how their institutions are preparing for AI usage(see chapter 2, page 29).

Institutional restrictions on the use of AI% Total(n=2,999)% Asia Pacific(n=894)% Europe(n=968)40

Don’t know / not sure33

29

Prohibited to upload
confidential information
into public generative
AI platforms

27

33

EU
NA
SA
MEA

23

Lack of budget to pay for
AI products or features

26

28

EU
NA

21

Prohibited to use it for
certain purposes

18

21

None of the above

11

9

Prohibited to use
certain tools

10

11

EU
SA

% North America(n=450)
AP
SA
MEA

38

SA
MEA

28

21

28

29

AP
SA
MEA

EU
SA
MEA

13

SA

35

EU
SA

AP
EU
NA

35

12

16

EU
SA
MEA

7

Other
(please specify)

2

1

2

AP
MEA

3

MEA
AP

3

Prohibited to use
it in any way

2

1

2

SA
MEA
AP

3

AP
SA
MEA

1

Significantly higher or lower than total

12

15

11

14

10

% Middle East
& Africa (n=193)

19

13

SA

% South America(n=451)

AP
NA

AP
EU
NA

18

EU
SA

15

AP

8

AP
MEA

0

0

Significantly higher than Role/ Region/ Country (indicated by first two letters e.g. AP = APAC)
Asia Pacific = AP
Europe = EUMid. East & Africa = MEA

North America = NA
South America = SA

China = CH
UK = UK
USA = US

RE = Researchers
CL = Clinicians

Fig 8. Question: Which restrictions, if any, does your institution currently have with regards to AI usage?

Insights 2024: Attitudes toward AI

17

Insights 2024: Attitudes toward AI

A future lens on AI

Chapter 2

A future lens on AI“AI is the future, but it is also very worrying.”
Survey respondent, doctor, Peru➤

95% think AI will help accelerate knowledge discovery➤

94% think AI will help rapidly increase the volumeof scholarly and medical research➤

92% foresee cost savings for institutions
and businesses➤

67% of those not using AI expect to use it in the next
two to five years➤

42% of those who have ethical concerns about AI
cite as a top disadvantage that it is unable to replace
human creativity, judgement and/or empathy➤

71% expect generative AI dependent tools’ results bebased on high quality trusted sources only

Insights 2024: Attitudes to AI

Researchers and clinicians recognize the growing
potential of AI tools, and if they’re not already using them,
most expect to do so in the coming two to five years.
Almost all respondents expect AI (including GenAI) to havean impact by helping accelerate knowledge discovery
and rapidly increasing the volume of research. While they
identify numerous benefits, they also note that AI will not
replace inherently human capabilities like creativity andempathy. Transparency and quality will be important in
the future as AI use increases.

19Perceived impact and benefits
The sentiment around AI is influenced by the impact
people expect the technology to bring in the future, someof it positive and some negative. In the current study,
almost all (96%) respondents think AI will change the way
education is delivered and 95% believe it will accelerateknowledge discovery at least to some extent
in the next two to five years.

impact positively, they are consistently less likely to
do so compared to other regions and indeed, for North
America, more likely to think AI will cause mishaps
and disruption than average globally (see Chapter 3
on page 32 and detailed findings in databook). Specifically,
95% of respondents see benefit in using AI for researchrelated activities (see figure 10).

Similarly, 94% of respondents think AI will rapidly increase
the volume of scholarly and medical research, withclinicians (96%) more likely than researchers (92%)
to think this. Although those in North America (and the
USA specifically) and Europe generally believe AI will
Positive impact of AI in various areas over the next two to five years% at least to some extent
Change the way students are taught and study in universities and medical schools

96

Accelerate knowledge discovery

95

Rapidly increase the volume of scholarly and medical research

94

Increase your work efficiency

92

Provide cost savings to institutions and businesses

92

Increase your work quality

87

Free your time for higher value work

85

Increase your work consistency

83

Increase collaboration79

Fig 9. Question: Thinking about the impact AI will have on society and your work, to what extent do you think over the next 2 to 5 years it will…?
A great extent, some extent, not at all. n=2,887

As noted in Elsevier’s 2022 Research Futures 2.0 report,“Artificial intelligence (AI) and machine learning tools
are changing the shape of science.” 28 Researchers today
can use GenAI-powered tools across a multitude of tasks,
including to:➤Collect, generate, sort and analyze data➤

Identify errors, inconsistencies and biases in data➤

Visualize data➤

Identify plagiarism➤

Discover relevant published research➤

Support peer review➤

Refine written work through translation and editing➤

Summarize and simplify academic papers➤

Brainstorm ideas for structuring presentations
and articles

Insights 2024: Attitudes toward AI

Drilling down into the detail of where AI may deliver
benefits across different areas, 95% of respondents
believe it will help with using scientific content(e.g., keeping up-to-date). The benefit of AI is also
expected to extend to human interaction, with 79%
of respondents (84% of clinicians and 74% of researchers)saying they think AI will increase collaboration(see detailed findings in databook for more detail).
“The single biggest topic must be AI. It is developing
so fast and has so many breakthroughs. I have to
study this topic myself. Artificial Intelligence will
promote unlimited possibilities for cross-disciplinary
collaboration.”
Academic Leader, APAC29

20

Perceived benefits of AI in different areas% No Benefit% Some benefit /A lot of benefit% Total(n=2,836)% Researchers(n=2,156)% Clinicians(n=964)

Data science activities

4

96

4

96

Using scientific content(e.g. keeping up-to-date)

5

95

7

93

3

97 RE

Teaching / lecturing activities

4

96

5

95

3

97

Clinical activities(e.g. clinical diagnoses, patient summaries)

5

95

5

95

Research related activities

5

95

5

95

Publication and monitoring impact of research8(e.g. authoring or reviewing) n=251 researchers who are also doctors

92

8

92

Funding related activities

84

17

83

10

90 RE

n=251 researchers who are also doctors

Significantly higher or lower than total

16

Significantly higher than Role/ Region/ Country (indicated by first two letters e.g. AP = APAC)
Asia Pacific = AP
Europe = EUMid. East & Africa = MEA

North America = NA
South America = SA

China = CH
UK = UK
USA = US

RE = Researchers
CL = Clinicians

Fig 10. Question: Thinking about the general areas of activity you need to complete, how much benefit, if any, do you believe the assistanceof AI would bring? Scale: A lot of benefit, some benefit, no benefit, don’t know/not applicable (bottom box and top two boxes, excl. don’t know)

Buying time for high-value work
As we have seen, GenAI is likely to have a bigger impact
on knowledge work than manual work. GenAI can play arole by automating structured tasks, reducing cognitive
load and supporting unstructured tasks like criticalthinking and creativity.30
According to the Office of National Statistics, about
one-third (32%) of UK adults believe that AI will benefit
them, rising to 49% of those with higher education
qualifications.22 This perception is largely down to thepotential GenAI has to improve work: 41% of professional
workers thought AI could make their job easier.
The expansion beyond purely data-related and repetitive
tasks is reflected in public surveys.31 For example,
consumers are using GenAI for creative purposes, likegenerating content (52%) and brainstorming (28%).
This is reflected in the current study: 85% of respondents
believe AI tools will free their time for higher value work,
though 15% don’t expect any impact in this area(see figure 9 on page 20).
For researchers and clinicians, it takes a lot of time andeffort to keep up to date with the influx of new knowledge
being published every day. The resulting ‘digital debt’builds up a backlog that can hide useful information andeven impact mental health. According to Microsoft’s
2023 Work Trend Index: Annual Report, 68% of people

Insights 2024: Attitudes toward AI“say they don’t have enough uninterrupted focus time
during the workday,” and 62% “struggle with too muchtime spent searching for information in their workday.”32
In the current survey, 95% of respondents see benefit in
AI using scientific content – in other words, keeping up todate with new information and reducing their digital debt.
Clinicians (97%) see more benefit than researchers (93%).
“Spend less time on papers doing the bureaucratic
part and can have a better reading about
the patient’s conditions.”
Survey respondent, nurse, Brazil33

In addition, 92% expect AI to increase their work
efficiency to some extent, and 92% expect the technology
to provide cost savings. This is echoed in research by
Capgemini, in which executives predicted operational
improvements of 7-9% within three years.23
About nine in ten (87%) respondents expect AI to improvetheir work quality to some extent, while 13% predict there
will be no impact in this area. Similarly,
83% think the technology will increase their work
consistency, compared to 17% who expect no benefit.

21

Powering education
GenAI already plays a role in education, and as such,many universities have set out policies and guidance
for students and educators. GenAI tools can support
learning by acting as “advisor, tutor, coach, andsimulator,” providing instructions, feedback anddifferent perspectives, for example.31
Almost all (96%) respondents to the current survey
expect AI to change the way students are taught to someextent, and a nearly all (96%) see at least some benefit
in AI for teaching and lecturing activities.
This is in line with findings from Clinician of the Future
2023, in which 51% of clinicians considered the use of
AI desirable for training medical students and 50%
for training nurses.34 And students reported similarsentiments, with 43% of respondents in the Clinicianof the Future Education Edition saying their instructors
welcome GenAI.35
The way today’s researchers and clinicians perceive andapproach using GenAI in teaching will affect not only its
impact on education but also on the views and behaviorsof the next generation of researchers and clinicians.

The results were striking, with a panel of licensed
healthcare professionals preferring ChatGPT’s responses
to physicians’ responses 79% of the time, rating themhigher quality and more empathetic.39

AI in publishing and funding
The publishing process – including authoring, reviewing
and editing – can be time-consuming for researchersand clinicians, and AI is already being employed inseveral systems.
Applications mentioned in Research Futures 2.0 include
StatReviewer, which has been integrated into Editorial
Manager, UNSILO’s AI-supported tools Evaluate Technical
Checks, integrated into ScholarOne, and AIRA, used
by Frontiers.40
There have been suggestions that the application of GenAI
could go even further, potentially even replacing humanreview, at least in part, in the future. In Research Futures
2.0, presented with this hypothetical scenario, 21% ofresearchers said they would be willing to read an article
reviewed by AI.41 Respondents shared reasons including
lower subjectivity and greater consistency across reviews.
“Some reviewers take a long time to respond.
An intelligent system would be much faster.”Supporting clinical activities
The potential applications of GenAI technology in theclinic are growing rapidly. The Research Futures 2.0
report highlights the use of AI in predicting the progressof Alzheimer’s disease, monitoring the progression ofParkinson’s disease, examining CT scans and x-rays,
diagnosing and developing personalized medication plansfor cancer patients, and improving the effectiveness ofmental healthcare.36
In the current study, 95% of respondents of those involvedin clinical practice see a benefit in AI for clinical activities
such as diagnoses and patient summaries. This is in linewith the views clinicians shared in 2023.37“AI can empower a trained physician to consider wider
differential diagnosis and management plan”.

Chemical Engineering researcher, Egypt40

However, the majority in the study – 59% – disagreed
or strongly disagreed that they would be willing to readan article reviewed by AI, many saying they “valued
human understanding and believed AI incapableof quality peer review.”
In the current study, 93% of respondents believe AI
will bring benefit in publication and monitoring theimpact of research, for example in authoring
and reviewing.
When it comes to funding, though, respondents were
not as optimistic, with 84% expecting AI to provide somebenefit for funding-related activities.

Doctor, UK38

Despite clinicians having reservations about the
impact of GenAI on the patient–clinician relationship(see page 31), blinded research reveals a more positive
picture. The study, by US researchers, asked the question:“Can an artificial intelligence chatbot assistant, provide
responses to patient questions that are of comparable
quality and empathy to those written by physicians?”

Insights 2024: Attitudes toward AI

22

Perceived drawbacks
Respondents were not solely positive about AI – theyalso identified a number of potential disadvantages of AI.
The majority (85%) had at least some concerns about
the ethical implications of AI in their area of work.

Clinicians (45%) are more likely to say this thanresearchers (39%). And women (46%) are more likely
to say this than men (38%).

People see its inability to replace human creativity,
judgement and/or empathy as the main disadvantage,
with 42% of those who have concerns about AI ranking
this as a top-three disadvantage of the technology.

“AI tools can help provide information and effective
management and nursing work, but it cannot replace
practical experience, interaction and communication
with patients.”
Survey respondent, nurse, China37

Perceived top-three disadvantages of AI (of those who have concerns)% Total(n=2,561)% Researchers(n=1,963)% Clinicians(n=861)

Unable to replace human creativity, judgment
and/or empathy

42

39

45

Does not have enough regulation or governance

40

39

41

Lack of accountability over the useof generative AI outputs

30

32

Outputs can be discriminatory or biased

24

25

Too dependent on outdated data
and/or information

19

21

CL

17

Outputs are factually incorrect and/or
non-sensical (hallucinations)

18

25

CL

11

Lack of relevant expertise within organisation

19

15

23

Risks homogenizing culture via its useof global models

18

17

18

The logic behind an output is not well described

17

20

Lack of permission to use data or information
AI tools are trained on

14

14

15

Generative AI inputs/prompts are
not confidential

13

12

14

Generative AI outputs are not confidential

11

10

11

Requires a lot of computer processing power

9

8

10

Generative AI discriminates against non-native
English speakers

7

7

7

Other

2

2

Don’t know/not sure

1

1

1

None of the above

0

0

0

Significantly higher or lower than total

CL

RE

29
23

CL

CL

RE

14

RE

1

Significantly higher than Role/ Region/ Country (indicated by first two letters e.g. AP = APAC)
Asia Pacific = AP
Europe = EUMid. East & Africa = MEA

North America = NA
South America = SA

China = CH
UK = UK
USA = US

RE = Researchers
CL = Clinicians

Fig 10. Question: What do you think are the top 3 disadvantages of AI? Select up to three?

Insights 2024: Attitudes toward AI

23

Regulation and accountability

Discrimination and bias

Two-fifths (40%) of respondents with concerns cite
the lack of regulation and governance as a top three
disadvantage of AI. Those in South America (45%) andEurope (45%) are most concerned. Indeed, there iscurrently a dearth of regulation for GenAI, largely due
to the speed at which the technology has developed –faster than policymakers can update laws.42

Following its inability to replace humans and the lack ofregulation and accountability around AI, the next mostcommonly cited disadvantage is that outputs can bediscriminatory or biased, with 24% of respondents withconcerns ranking this in their top three.

This concern about a lack of regulation is widespread,even among the corporate leaders driving the GenAI
movement, with the CEOs of OpenAI and Google and
the President of Microsoft among those taking steps
to encourage regulation.43 Senate Judiciary Committee
Chairman Richard Durbin said it is “historic” for “people
representing large corporations [to] come before us andplead with us to regulate them.” 44
One of the benefits of regulation is highlighting thepotentially negative effects of GenAI, and as Joshua
Gans, co-author of Power and Prediction: The Disruptive
Economics of Artificial Intelligence, shared in aninterview with the International Monetary Fund (IMF),“it behooves us to monitor for those consequences,
identify their causes, and consider experimentation with
policy interventions that can mitigate them.” 45
The need for better guidance and oversight is reflected
in two other top three disadvantages. About one-third(30%) of respondents with concerns ranked lack of
accountability over the use of AI outputs in their top three;this is highest in North America (34%), and researchers(32%) are more likely than clinicians (29%) to cite this as a
top concern. Conversely, clinicians (23%) were more likely
than researchers (15%) to cite ‘lack of relevant expertise
within organizations’ as a top disadvantage of AI.

Early days of regulation: The EU’s AI Act46
Agreed in December 2023, the AI Act aims to address
the risks certain AI systems can create in order toavoid “undesirable outcomes.”

For almost one-fifth (18%) of respondents, the risk of AI
homogenizing culture via its use of global models is a
top three disadvantage, and 7% of respondents cite thetechnology’s discrimination against non-native English
speakers.
The concern about bias and discrimination in AI is notnew. As noted by the UK’s communications regulator
Ofcom, if the voices and perspectives of marginalizedgroups are underrepresented in training data, GenAI
models can underrepresent them in outputs, leading
to exclusion and inaccurate information about thosegroups.47 Tech leaders have acknowledged the problem
and recognize the need for improvement.48 To overcome
this, Ofcom suggests that the datasets used to train GenAI
models should be “diverse and representative,” which will
require human quality control.
Capgemini research revealed that 45% of organizations
lack confidence that GenAI programs are fair (inclusiveof all population groups) and 36% say the potential forbias to lead to embarrassing (i.e. undesirable or socially
unacceptable) results is a challenge for implementing thetechnology.23“I suspect that AI will be easier to reprogram to be lessdiscriminatory than people are.”Joshua Gans45

Conversely, there are some indications that GenAI has thepotential to make a positive impact on existing biases anddiscrimination. According to the Pew Research Center, 51%
of US adults who see a problem with racial and ethnic bias
in health and medicine think AI would improve the issue,and 53% believe the same for bias in hiring.18

The Regulatory Framework defines four levels of risk
for AI systems. An AI system will be banned if it is“considered a clear threat to the safety, livelihoods
and rights of people.” This includes, for example,
social scoring by governments and toys encouraging
dangerous behavior.
The European AI Office oversees the enforcement
and implementation of the AI Act.

Insights 2024: Attitudes toward AI

24

Lack of accuracyMore insight into the datasets used to train GenAI models
would not only help mitigate against the potential for bias
but also give transparency around how an output was
generated. A number of respondents to the current survey(17%) consider ‘the logic behind an output is not welldescribed’ as a top-three disadvantage. Researchers (20%)
are more likely than clinicians (14%) to rank this issue intheir top three.
Accuracy was more important to respondents thantransparency. For 19% overall, being too dependent
on outdated data and/or information is a top three
disadvantage of AI. Researchers (21%) are more likely
than clinicians (17%) to rank this highly.
Similarly, 18% of respondents with concerns consider
hallucinations (i.e. when AI generates incorrect and/or
nonsensical outputs) to be a major disadvantage, withresearchers (25%) significantly more likely than clinicians(11%) to rank this in their top three.
Hallucinations are incorrect and sometimes nonsensicaloutputs generated based on patterns in training data,
and they occur in an estimated 3% to 30% of answers.49
Hallucinations are a topic of discussion among techleaders as well as users. According to Sundar Pichai,CEO of Alphabet, “No one in the field has yet solved
the hallucination problems. All models do have thisas an issue.”50 Given their ubiquity, hallucinations areof particular concern for areas like law and medicine,according to some researchers.31

Privacy and ethical issues
Some of the less commonly ranked disadvantages
are related to privacy and ethical issues. For example,
13% of respondents with concerns consider the lack ofconfidentiality of AI inputs or prompts as a top-three
disadvantage, and 11% rank the lack of confidentialityof outputs as such.
Privacy is one of the main concerns of consumers, with
72% of the UK public surveyed by the Office of National
Statistics considering the use of personal data without
consent a negative impact, and 60% mentioning theincreased chances of experiencing cybercrime.22
Looking at the data ownership issue from the other side,
14% of respondents in the current study say the lack ofpermission to use data or information AI tools are trained
on is a top three disadvantage. And almost one in ten(9%) respondents consider AI’s need for a lot of computer
processing power to be a top-three disadvantage.

Insights 2024: Attitudes toward AI

25

Expectations
As noted in chapter 1, more than half of respondents in thecurrent study have used AI, either for a work or non-work
purpose (see page 10). This is likely to change soon: 67%of those who have yet to use AI (including GenAI) tools
expect to do so in the next two to five years.
The proportion of those in North America (and in the USA
specifically), who have yet to use AI, is notably lower - only
51% expect to do so in the near future, significantly lower
than the global average and highest in APAC and Middle
East and Africa.
While respondents were optimistic about their future useof AI, they also shared a number of expectations aroundhow they believe AI should develop.
The top expectation overall is that generative AI will
always be paired with human expertise, with 83% of
respondents globally agreeing with this. Clinicians (86%)
are more likely than researchers (81%) to agree.

Expected future use for those that currently don’t use AI% Total(n=1,330)% Asia Pacific(n=373)

Yes

67

76

No

6

3

6

AP

Don’t know/not sure

27

22

39

AP
NA
SA
MEA

Significantly higher or lower than total

EUNA% Europe(n=450)% North America(n=209)% South America(n=192)

55

51

72

18

31

AP
NA
SA
MEA

4

AP
MEA

25

EU
NA

% Middle East
& Africa (n=84)
EU
NA

81

5

MEA

15

Significantly higher than Role/ Region/ Country (indicated by first two letters e.g. AP = APAC)
Asia Pacific = AP
Europe = EUMid. East & Africa = MEA

North America = NA
South America = SA

China = CH
UK = UK
USA = US

RE = Researchers
CL = Clinicians

Fig 12. Question: Do you expect you will choose to use AI in the near future?

Insights 2024: Attitudes toward AI

26

Expectations of AI% Disagree% Total(n=2,836)% Agree% Researchers(n=2,156)% Clinicians(n=964)Generative AI to always be paired with humanexpertise (i.e. qualified people validate outputs)

7

83

9

81

6

86

To be informed whether the tools I use dependon generative AI

6

81

6

81

6

81

To be given a choice to turn off generative
AI in the tools that I use

9

75

9

76

8

74

Generative AI will work well with non-text modalities (i.e. chemical or biological compounds,chemical reactions, graphs, plans)

8

74

10

72

7

77

RE

Generative AI dependent tools’ results be basedon high quality trusted sources only

6

71

6

68

6

73

RE

Significantly higher or lower than total

RE

Significantly higher than Role/ Region/ Country (indicated by first two letters e.g. AP = APAC)
Asia Pacific = AP
Europe = EUMid. East & Africa = MEA

North America = NA
South America = SA

China = CH
UK = UK
USA = US

RE = Researchers
CL = Clinicians

Fig 13. Question: Thinking about the use of generative AI in your area of work, how much do you agree or disagree with the following either presently
or in the near future? By near future, we mean in the next 2-5 years.

Information and consent are critical: 81% of respondents
expect to be informed whether the tools they use dependon generative AI, and 71% expect AI tools’ results to be
based on high quality trusted sources
Three-quarters (75%) of respondents expect to be given a
choice to turn off generative AI in the tools that they use.
Respondents expect generative AI will work well with nontext modalities (i.e. chemical or biological compounds,chemical reactions, graphs, plans) (74%); agreement ishigher among clinicians (77%) than researchers (72%).

Quality is important too: about seven in ten (71%)
respondents expect generative AI dependent tools’
results to be based on high quality trusted sources only,with agreement higher among clinicians (73%) thanresearchers (68%). This aligns with the findings sharedearlier in this chapter, with researchers more likely toconsider outdated source information a top disadvantage(see page 23).

Likelihood of using a reliable AI assistant by those who see benefit of AI in research

94%

91%

89%

Review prior studies, identify gaps
in knowledge and generate a newresearch hypothesis for testing

Prepare your paper

Synthesize publishedresearch articles

Fig 14. Question: If you had a reliable and secure AI assistant to help you in your research, how likely would you be to use it to...
Scale: Very likely, Likely, Somewhat likely, Unlikely, Not at all likely, Don’t know, Not applicable (top 3 box excluding ‘don’t know’
and ‘not applicable’ answers). n=1008, 568 and 936

Insights 2024: Attitudes to AI

27

Researchers believe AI can bring benefit across a rangeof activities, including developing new ideas, preparing
articles and summarizing information. Of those who think
AI would benefit research activities or using scientificcontent, 94% are likely to use a reliable AI assistant toreview prior studies, identify gaps in knowledge andgenerate a new research hypothesis for testing, 91% toproof their paper and 89% to generate a synthesis ofresearch articles in an area.
Likelihood of using a reliable AI assistant to help
assess symptoms

94%
Reviewpriorastudies,
identify
gaps
Fig 15. Question:
If you had
reliable andsecureAI assistant toin knowledge
andlikely
generatenewhelp you in clinicalactivities, howwouldayou
be to use it to…
research hypothesis for testing
Assess symptoms and identify possibility of a disease/condition(provides confidence levels for diagnosis and recommends any
confirmatory tests). Scale: Very likely, Likely, Somewhat likely, Unlikely,
Not at all likely, Don’t know, Not applicable (top 3 box excluding ‘don’t
know’ and ‘not applicable’ answers). n=687 shown to clinicians whobelieve AI can bring benefit when completing clinical activities

For clinicians, who believe AI could bring benefit acrossclinical activities such as diagnoses and clinical imaging,
94% are likely to use a reliable and secure AI assistant toassess symptoms and identify a disease or condition.

Insights 2024: Attitudes toward AI

Institutions are preparing for
an AI-powered future
Looking to the future, institutions are also expecting theuse of GenAI to increase – and they’re preparing for it.
Elsevier’s report View from the Top: Academic Leaders’ andFunders’ Insights on the Challenges Ahead highlights thatmany universities have GenAI guidelines in place, or are
working on them, both for research and education.51 In
particular, 64% of academic leaders are prioritizing thechallenge of AI governance, though only 23% consider
their institutions well prepared to tackle the challenge.52“AI is going to change everything about how we workat universities, particularly in the teaching but also, in
the research. I don’t think we have begun to scratch thesurface of what that looks like.”

91%

89%

Academic leader, EMEA53

Businesses more broadly are taking the subject seriously.
Capgemini reports that GenAI is on the boardroom
agenda for 96% of organizations, with one-fifth ofexecutives expecting the technology to “significantly
Prepareyourtheir
paperindustries.”23 Support is even
Synthesize
publisheddisruptstrongeramong
research articles
pharma and healthcare companies: 98% of executives inthis industry say GenAI is on the board’s agenda, and 58%
say company leaders are strong advocates of GenAI.
As such according to Capgemini 97% of organizations hadplans for GenAI and by July 2023, 40% of organizations
had set up teams and allocated budget to GenAI (42%for the pharma and healthcare sector). A further 49%
planned to do so within a year.23 More than two-thirds(68%) reported establishing guidelines and policies on
employees’ use of GenAI, and 10% had banned, or wereconsidering banning, GenAI tools.

28

In the current study, actions institutions are taking include
building a plan or protocol to evaluate the purchase oftools that include AI (reported by 16% of respondents),
setting up a community of practice around it (14%) andproviding ethics courses (14%). Overall, 12% plan toacquire tools that include AI in 2024 or beyond.

It is less common for institutions to be appointing
new AI leadership (6%) or operational functions suchas GenAI Librarian (10%).

Ways in which institutions are preparing for AI usage% Selected
Don’t know / not sure44

Building a plan/protocol to evaluate the purchase of tools that include it

16

Setting up a community of practice around it

14

Providing ethics courses

14

None of the above

13

Planning to acquire tools that include it (within 2024 or before)

12

Adding a position around it to your documentation (e.g. annual plan, mission, charter etc..)

11

Appointing new operational functions around it (e.g. GenAI Librarian etc..)

10

Appointing new leadership around it (e.g. Chief AI Officer etc..)
Other (please specify)

62

Fig 16. Question: In which ways, if any, is your institution preparing for AI usage? n=2,999

Insights 2024: Attitudes toward AI

29

Insights 2024: Attitudes toward AI

Shaping an AI-driven future

Chapter 3

Shaping an AI-driven future“We’re only at the beginning of what AI canaccomplish. Whatever limitations it has today will begone before we know it.”
– Bill Gates2➤

94% believe AI could be used for misinformation➤

86% are concerned AI could cause critical errors
or mishaps➤

81% think AI will to some extent erode critical thinking
with 82% of doctors expressing concern physicians
will become over reliant on AI to make clinicaldecisions➤

58% say training the model to be factually accurate,
moral, and not harmful (safety) would strongly
increase their trust in that tool➤

Knowing the information the model uses is up to date
was ranked highest by respondents for increasing
their comfort in using an AI tool

Understanding not only their concerns but also the factorsthat build researchers’ and clinicians’ trust in AI tools andtheir comfort using them can help technology developers
create better tools and institutions maximize their benefit.
Almost all respondents are concerned that AI will be
used for misinformation, a concern that was identified in
Elsevier’s Confidence in Research global survey,56 as well as
cause critical errors or mishaps.

Factual accuracy and up-to-date models and information
would help increase trust among users.

Exploring users’ concerns
The potential of GenAI is becoming clearer as thetechnology develops, as are the potential pitfalls.
GenAI tools can be powerful, not only for automating
structured tasks and accelerating data analysis andvisualization but also developing hypotheses andsupporting clinical decisions.
When the stakes are high, as they are in the treatment ofpatients, it is vital that technology is responsible, ethicaland transparent. Concern about the loss of the humanelement is particularly high around the use of AI in
healthcare, and most Americans think it could harm thepatient–clinician relationship.18
In a Pew Research survey, 60% of adults said they would
feel uncomfortable if their healthcare provider relied on
Insights 2024: Attitudes toward AI

AI for their medical care, and opinion was split about thehealth outcomes, with 38% expecting them to be betterand 33% worse.18
This provides a dilemma for tech companies developing
the technology as well as those using it: they need tomove fast to keep up with the changing landscape andharness the potential for innovation, but they also need
to be cautious about the risks, many of which are still
unknown.10
Understanding users’ (and potential users’) concerns
around GenAI is an important step in developing tools
with minimized risks. Some of the biggest concerns arearound misinformation and errors.

31

Researchers’ and clinicians’ concerns
Overall, 94% of respondents (95% of researchers and 93%
of clinicians) believe to some extent that AI will be used for
misinformation over the next two to five years.
“These tools are not yet based on scientific evidence, do
not provide references, and are not yet reliable.”

GenAI technology can be used to produce misinformation,and if trained with this data, it can use misinformation
as a basis for outputs it considers true. As Ofcom notes,“generative AI models are not capable of determining thetruth or accuracy of information on their own.”47 Users are
not always aware of the misinformation they collect, suchas in the case of a lawyer cited for using fictitious case law
in a legal brief that he used GenAI to write.30

Survey respondent, doctor, Brazil

This makes the governance and regulation of GenAI
even more vital, and institutions have a role to playin mitigating the intentional use of GenAI to produce
misinformation. As noted in View from the Top: Academic
Leaders’ and Funders’ Insights on the Challenges Ahead,academic leaders are concerned about how to mitigate
risks like the falsification of research results.54
Most researchers and clinicians (86%) are also worried
about critical errors or mishaps (accidents) occurring, with
14% not expecting this not to happen at all.
However, previous research suggests particular concern
about mistakes in healthcare resulting from AI use,with over three-quarters of US clinicians considering
it important for tech companies and governments tocarefully manage AI applications in disease diagnosis.26“I am very worried about generative AI leading toclinical mistakes that could harm patients. Thesemachines don’t think, they recognize patterns to makeconfident but nonsensical answers. That is dangerous
when making decisions. Lawyers are already in deep
legal trouble for trying to pass off generative AI
documents as their work.”
Survey respondent, doctor, USA

Negative impact of AI in various areas over the next two to five years% At least to some extent
Be used for misinformation

94

Cause critical errors or mishaps (e.g. accidents)

86

Physicians become over reliant on AI to make clinical decisions (doctors only n=673)

82

Erode human critical thinking skills

81

Cause disruption to society (e.g. unemployment for large numbers of people)

79

Fig 17. Question: Thinking about the impact AI will have on society and your work, to what extent do you think over the next 2 to 5 years it will…?
A great extent, some extent, not at all. n=2,829

Insights 2024: Attitudes toward AI

32

When technology meets humanity
Several other concerns relate to the impact GenAI could
have on people and the way they think and behave.
In the current study, 81% of respondents think AI will
erode human critical thinking skills. Indeed, there issuggestion of a risk that AI will affect the way students
think, which any changes in curriculum should consider.55
Over four in five (82%) doctors think use of AI may mean
physicians become over reliant on the technology to makeclinical decisions. This concern was echoed in the Clinicianof the Future Education Edition, in which more than half(56%) of students feared the negative effects AI can haveon the medical community.35

Social disruption is a concern for 79% of respondents,for example with AI causing the unemployment of large
numbers of people.
Ethical concerns are also important: in the current survey,
most respondents (85%) have at least some concerns,
with only 11% reporting no concerns about the ethicalimplications of AI on their area of work and 11% reporting
fundamental concerns. This is higher in Europe (17%) andNorth America (14%) (see detailed findings in databook).

Level of concerns about the ethical implications of AI% Total(n=2,999)
No concerns% Researchers(n=2,284)

11

12

11

Some concerns

47

Significant concerns

50

27

Fundamental concerns

44
28

RE

11

11

4

Significantly higher or lower than total

CL

25

11

Don’t know/not sure

% Clinicians(n=1,007)

5

4

Significantly higher than Role/ Region/ Country (indicated by first two letters e.g. AP = APAC)
Asia Pacific = AP
Europe = EUMid. East & Africa = MEA

North America = NA
South America = SA

China = CH
UK = UK
USA = US

RE = Researchers
CL = Clinicians

Fig 18. Question: To what extent, if at all, do you have concerns about the ethical implications of AI (including generative AI) in your area of work?

Factors impacting trust in AI tools“I’m distrustful of all AI tools at present. It would takea lot of transparency along with concrete examples of
the tool in action to convince me it is trustworthy. My
career and my scientific integrity are too valuable tohand over to anyone or anything else. I am also notprotected by tenure so any slip-ups and I will lose
my career.”
Survey respondent, researcher, Canada

Insights 2024: Attitudes toward AI

When combined, the potential GenAI has for
misinformation, hallucinations, disruption to society
and impact on job security paints a picture for many of atechnology that is difficult to trust.25 Yet surveys show thatmost people do trust the technology.
The Capgemini Research Institute found that 73% ofconsumers trust content created by GenAI.20 Specifically,
67% believed they could benefit from GenAI used for
diagnosis and medical advice, and 63% were excited by
the prospect of GenAI bolstering drug discovery.

33

What makes researchers and clinicians
trust AI?
There is room for improvement when it comes to trust.
Respondents to the current survey share their views about
how to build trust in AI tools, and views are similar for
researchers and clinicians across all factors.

Some of the other factors respondents say would increase
their trust in AI tools relate to quality and reliability. For
example, 57% say only using high-quality peer-reviewed
content to train the model would strongly increase theirtrust, while just over half (52%) say training the modelfor high coherency outputs (quality model output) would
strongly increase their trust.
Transparency and security are also important factors.
For 56% of respondents, citing references by default(transparency) will strongly increase trust in AI tools.
Keeping the information input confidential is a trustboosting factor for 55%, as is abidance by any laws
governing development and implementation (legality)
for 53%.

More than half (58%) of respondents say training themodel to be factually accurate, moral and not harmful
would strongly increase their trust in that tool.

Statement: Factors that strongly increase trust in AI tools% No impact% Strongly increase my trust% Total(n=2,847)% Researchers(n=2,164)% Clinicians(n=960)Training the model to be factually accurate,
moral, and not harmful (safety)

6

58

8

57

5

59

Only using high-quality peer-reviewed content
to train the model (quality model input)

6

57

7

56

4

58

Citing references by default (transparency)

7

56

8

56

6

57

Keeping the information input confidential(security)

10

55

13

55

7

55

Abidance by any laws governing development
and implementation (legality)

8

53

10

52

5

54

Training the model for high coherency outputs(quality model output)

7

52

8

52

5

53

Significantly higher or lower than total

Significantly higher than Role/ Region/ Country (indicated by first two letters e.g. AP = APAC)
Asia Pacific = AP
Europe = EUMid. East & Africa = MEA

North America = NA
South America = SA

China = CH
UK = UK
USA = US

RE = Researchers
CL = Clinicians

Fig 19. Question: To what extent, if at all, would the following factors increase your trust in tools that utilize generative AI? Scale: Strongly increase
my trust, Slightly increase my trust, No impact on my level of trust

The importance of accessRegional differences across many survey
questions highlight the importance of accessin the implementation of AI globally.
Respondents in lower-middle-income countries are
significantly more likely than those in high income
countries to think AI will increase collaboration,
at 90% and 65% respectively. They are also more
likely to think AI will be transformative, at 32%
compared to the global average of 25%.

Insights 2024: Attitudes toward AI

However, respondents are less likely to have used
AI for work purposes (at 21% versus the averageof 31%), perhaps owing to access issues. While 26%of respondents globally cite a lack of budget
as a restriction to using AI, this increases to 42%
in lower- middle-income countries.

34

Actions for an AI-powered future“All emerging technologies, including AI, have bothadvantages and disadvantages. It is essential to further
develop and regulate these technologies, aiming to
extract maximum benefits.”
Survey respondent, researcher, Canada

Respondents to the current survey clearly share theview that the AI tools they use now and in the future to
support research and clinical work should be responsible,
ethical and transparent. With this in mind, information,consent and quality are critical factors to consider fromdifferent angles.

GenAI technology providers

Increase transparency
Respondents expect to be informed whether the tools they
are using depend on GenAI (81%) and would want theoption to turn off the functionality (75%). In line with their
expectation that it should be possible to choose whether
to activate AI functionality, 42% of respondents would
prefer AI to be provided as a separate module, while 37%
would want it integrated into a product.
Solution providers should be clear about the datasets
used, and ensure intellectual property and copyright isprotected. GenAI functionality should be clearly labelled
or otherwise indicated, ideally with the ability for users
to switch it off and on.
Strengthen safety and security

Enhance accuracy and reliability
As we saw in Chapter 2 (see figure 13 on page 27),
researchers and clinicians expect tools powered by GenAI
to be based on high-quality, trusted sources only (71%).
To support this, developers should work to ensure thedatasets used to train GenAI tools are reliable, accurate
and unbiased. To minimize bias, advanced NLP techniques
could be applied to understand the intent of users formore relevant outputs.20 Efforts to minimize the risk ofhallucination should continue.

As regulation and policy develops, tech companies havea role to play in ensuring the safety of their GenAI tools,
including robust governance and human oversight.
Given the importance of privacy and data security,
developers could go beyond regulation to ensure
their tools are safe and secure for users, thereby
increasing trust.

Access preference for AI tools% Total(n=2,148)% Researchers(n=1,346)

Provided as a separate module

42

Integrated into the productDon’t know/not sure
Significantly higher or lower than total% Clinicians(n=802)
43

41

37

39

36

21

23

CL

19

Significantly higher than Role/ Region/ Country (indicated by first two letters e.g. AP = APAC)
Asia Pacific = AP
Europe = EUMid. East & Africa = MEA

North America = NA
South America = SA

China = CH
UK = UK
USA = US

RE = Researchers
CL = CliniciansFig 20. Question: Would you prefer any generative AI functionality included in a product you use already to be…?

Insights 2024: Attitudes toward AI

35

Institutions employing researchersand clinicians
Establish policies and plans and communicate
them clearly
As we have seen, numerous organizations are working on
policies, guidance and plans to integrate GenAI into theiroperations. However, as respondents shared in the survey,
many are unaware of their institutions’ plans, including
restrictions on using GenAI.
In addition to establishing guidelines on GenAI
and taking steps towards a strategy for the organization,communicating those actions and plans to researchersand clinicians would help mitigate risk andmaximize benefit.
Build governance and expertise
Institutions can help increase the comfort and trustof researchers and clinicians in GenAI by ensuring thetools they choose are overseen in a way that identifies
and reduces biases and risks.
Any GenAI strategy should include a robust governancestructure, including people with expertise in thetechnology and its area of application.

Insights 2024: Attitudes toward AI

Provide training and capacity
Despite its rapid increase in awareness and usage,
GenAI remains a relatively young technology.
As the use of GenAI increases, researchers and clinicians
will need to spend time learning how to maximize
its benefit. Previous research with clinicians has
highlighted the potential burden of AI due to therequired time to learn.34
To ensure the technology is part of the solution rather
than the problem, institutions could identify ways to give
researchers and clinicians the time and a safe space toexplore GenAI.
Ensure access
AI perception is markedly more positive in lower-middleincome countries, yet its use among researchers andclinicians is limited due to budgetary restrictions.
Institutions are increasingly aware of the importanceof inclusion, and the role accessibility plays in that.
As use of AI becomes increasingly widespread globally,
there will be a growing need to address gaps in access tothe technology, especially in international collaboration.
To help ensure improved access to AI technology globally,
institutions could consider AI as part of their wider
strategy, to help foster partnership and ensure greater
diversity at the institutional and project level.

36

Insights 2024: Attitudes toward AI
Conclusion
Building on previous research published in the Research
Futures and Clinician of the Future series, this report setsa baseline for researchers’ and clinicians’ awareness,
perspectives, use, concerns and expectations of AI(including GenAI).
In Research Futures 2.0, we outlined the ‘Tech titans’scenario, in which “significant advances in AI products
drive innovation, enabling technology companies tosupport the research ecosystem and become knowledge
creators and curators.”
Since then, we have seen the potential of AI jump forward
considerably with the arrival of generative AI into public
consciousness through the launch of ChatGPT3 in late2022. This was a watershed moment, as it gave mostof the public, as well as researchers and clinicians,a glimpse into its potential.
Whilst the majority of researchers and clinicians
are aware of AI and over half (54%) of those surveyedhave actively used it, and just under one-third (31%)
for a specific work-related purpose, few are actively
using AI tools often.
Many see its great potential to accelerate knowledge
discovery, increase work quality and save costs. But they
are worried about AI’s potential for misinformation, tocause critical errors and to erode critical human thinking.
The implicit expectation from respondents to our survey
is that providers of AI tools take appropriate measures tomitigate the potential negative impacts of AI and for the
majority transparency and AI tools being based on highquality trusted resources are critical.

Elsevier’s role
Elsevier provides information-based analytics anddecision tools for researchers and health professionals
worldwide, helping them advance science and improvehealthcare outcomes, for the benefit of society.

Insights 2024: Attitudes toward AI

For more than a decade, Elsevier has been using AI andmachine learning technologies responsibly in our products
combined with our unparalleled peer-reviewed content,
extensive data sets, and sophisticated analytics to help
researchers, clinicians and educators discover, advanceand apply trusted knowledge.
Our responsible AI principles➤

We consider the real-world impact of our solutions
on people.

➤

We take action to prevent the creation or
reinforcement of unfair bias.

➤

We can explain how our solutions work.

➤

We create accountability through human oversight.

➤

We respect privacy and champion robust data
governance.

Whatever future we head towards, it is clear that GenAI
will play a role. The aim of this study was to understandthe AI landscape from the point of view of researchers andclinicians, including their awareness, perception and useof GenAI tools. With these insights into their concerns andexpectations, we at Elsevier together with institutions we
support are better prepared to utilize AI to help advanceknowledge and health care.
As familiarity with GenAI grows, parallel with
developments in the technology, areas of opportunity andconcern are likely to evolve. We will continue to monitor
researchers’ and clinicians’ views and behavior to meettheir needs with responsible AI tools that support researchand clinical decisions.

For further information go to:https://tinyurl.com/ai-attitudes
Follow Elsevier Connect on
X (formerly Twitter), Facebook and LinkedIn

37

Insights 2024: Attitudes toward AI
Methodology
This study aimed to uncover awareness, usage andperceptions of AI, including generative AI.
In late December 2023 to February 2024, Elsevier senta survey to a sample of people working in research(including leaders and corporate researchers) and in
health (clinicians) from a variety of sources, including:➤Those who had published recently – these
individuals were randomly selected froma database of published authors across journals
and books from various publishers➤

A third-party panel provided by Dynata(voluntary sign up)➤

Users of Elsevier solutions as well as from
Elsevier’s marketing databases

Participants were recruited using an email invitation
containing a link to the online survey. A total of 2,999
people from 123 countries and a range of disciplines
completed the survey. Clinicians undertaking researchas part of their role count as both clinicians andresearchers. Base sizes shown in the report
are unweighted.

Insights 2024:
Attitudes toward AI
When:
When:
Who:

December 2023 to February 2024
15-min online quantitative survey
Global study with 2,999 responses from123 countries.
= 2,284 researchers= 1,007 clinicians(of whom 292 are also included as researchers)

Results: To increase representativeness responses weweighted based on OECD and Pharma
Factbook population figures by region,and to equally represent researchers andclinicians in totals. Clinicians areweighted equally by doctors and nurses.
Base sizes included in the report are
unweighted.

Results are weighted based on OECD/Pharma Factbook
population figures for Researchers and Clinicians byregion, and to equally represent Research and Healthsectors in the totals. Health is weighted 50:50 medicine
and nursing.
Despite the weighting, the study is not without limitations
due to self-selection, non-response biases and the lower
response rate than what is typical for online surveysof this nature. Therefore, there will be some non-sampling
error associated with this study, as we cannot be sure
responses accurately represent the views of the population
for a given country. Statistical differences shown in thisreport should be interpreted within this context, andwhile showing notable difference between groups, results
are not necessarily generalizable to a whole country.
Given the non-probability sampling methods, these tests
are indicative.

Insights 2024: Attitudes toward AI

38

Insights 2024: Attitudes toward AI
Appendices
Sample bases by region/country
NB. Clinicians undertaking research as part of their role count as both clinicians and researchers.
ASIA-PACIFIC
Afghanistan
Australia
Bangladesh
Cambodia
China
Fiji
French Polynesia
Hong Kong
India
Indonesia
Japan
Malaysia
Mongolia
MyanmarNepal
New ZealandPakistan
Philippines
Singapore
Solomon Islands
South Korea
Sri Lanka
TaiwanThailand
VietnamTotal

Researchers
1
26
3
1
311
1
0
3
101
13
112
17
1
1
1
1
14
10
3
1
68
4
37
14
1
745

Insights 2024: Attitudes toward AI

Clinicians
0
16
2
0
103
1
1
0
42
6
27
4
0
0
1
3
5
14
3
0
9
3
20
0
2
262

Total
1
37
4
1
358
2
1
3
134
18
120
21
1
1
2
4
16
23
5
1
73
6
45
14
3
894

EUROPE
Albania
Armenia
Austria
Azerbaijan
Belgium
Bulgaria
Croatia
CyprusCzech Republic
Denmark
FinlandFranceGeorgia
Germany
GreeceHungary
Iceland
Ireland
Italy
Kazakhstan
Kyrgyzstan
LatviaLebanonLithuania
Malta
Netherlands
NorwayPolandPortugal
Romania
RussiaSerbiaSlovenia
Spain
SwedenSwitzerland
TurkeyUkraineUnited Kingdom
Uzbekistan
Total

Researchers
2
1
6
2
8
4
3
1
7
8
11
100
4
63
4
6
1
2
39
5
1
2
2
1
1
22
10
36
13
7
131
9
4
106
7
13
55
10
47
4
758

Clinicians
0
0
4
0
0
1
1
1
1
2
1
42
0
27
2
0
0
0
12
0
1
0
0
0
0
13
1
3
4
1
8
3
0
138
4
5
6
0
13
0
294

Total
2
1
8
2
8
5
4
2
8
8
11
126
4
82
6
6
1
2
44
5
1
2
2
1
1
32
11
38
16
8
135
10
4
219
9
16
61
10
53
4
968

39

Insights 2024: Attitudes toward AI
AppendicesMID. EAST & AFRICA
Algeria
Bahrain
Botswana
Burkina Faso
Cameroon
Côte d’Ivoire
Egypt
Ethiopia
Gambia
Ghana
Iran
Iraq
IsraelJordanKenya
KuwaitMoroccoMozambique
Nigeria
Oman
Palestinian Authority
RéunionRwandaSaudi Arabia
SenegalSouth Africa
Sudan
Syria
Togo
Tunisia
UgandaUnited Arab Emirates
ZambiaZimbabwe
Total

Researchers
2
1
1
2
3
2
15
4
1
3
45
5
6
11
4
0
4
1
16
2
2
1
2
7
2
3
0
2
1
3
5
6
2
1
165

Clinicians
0
0
0
0
1
2
2
1
0
5
7
0
1
0
3
2
1
0
4
1
0
1
2
3
0
3
1
0
1
2
0
2
0
0
45

Total
2
1
1
2
3
3
16
4
1
6
49
5
6
11
7
2
5
1
20
3
2
1
2
9
2
6
1
2
1
3
5
8
2
1
193

PREFER NOT TO SAY COUTRY
Total

Researchers
35

Clinicians
14

Total
43

GRAND TOTAL
Total

Researchers
2,284

Clinicians
1,007

Total
2,999

Insights 2024: Attitudes toward AI

NORTH AMERICA
Researchers
Canada49
United States of America
298
Total
347

Clinicians
14
127
141

Total
57
393
450

SOUTH AMERICA
Argentina
Bolivia
BrazilChile
Colombia
Costa Rica
Cuba
CuraçaoDominican Republic
EcuadorEl Salvador
GuatemalaHaiti
Honduras
MexicoNicaragua
PanamaParaguay
Peru
Puerto Rico
Uruguay
Venezuela
Total

Clinicians
32
2
19
12
21
4
1
1
1
21
2
3
1
2
85
7
3
1
20
0
8
5
251

Total
48
3
96
25
38
5
3
1
1
30
3
4
1
2
134
8
3
1
27
1
9
8
451

Researchers
17
1
81
18
19
1
2
0
0
13
1
2
0
1
57
1
1
0
9
1
4
5
234

40

Acknowledgments
Sponsors

Report Communications

Kieran West

Andrew Davis
Chris WestDan DiPietro-JamesDavid Tucker
Terri Mueller
WE Communications

Program Team
Adrian Mulligan
Jose Sevilla IV
Katrina Santos
María Aguilar Calero
Nicola Mansell
Tawkir Kamali
Report Authors
Adrian Mulligan
María Aguilar Calero
Nicola Mansell
Lucy Goodchild (lead author)
TellLucy.com

Insights 2024: Attitudes toward AI

Report Design
Craig Unsworth
Emma Ahlqvist
David Rickels DR Design Associates
Thanks also to various Elsevier staff
who provided valuable support on
this report.

41

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Insights 2024: Attitudes to AI
Elsevier July 2024