sidhellman/clean_data.txt · Datasets at Hugging Face

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widespread digitalization and may continue to do so.
In addition, newer companies, notably fintechs, do not
face this issue. The burden of legacy technology will
therefore likely diminish, a process that generative AI, if
anything, can accelerate.
As is the case with any new technology, talent with
expertise specifically in generative AI is in short supply
across the economy. For now, financial services
companies appear to be training staff rather than
bidding to recruit from a sparse specialist pool. That
said, the difficulty in finding AI talent is already starting
to ebb, a process that would mirror those seen with the
rise of cloud and other new technologies.
More difficult to overcome may be weaknesses in
the technology itself and regulatory hurdles to its
rollout for certain tasks. Financial services companies
aiming to benefit from generative AI face several
hurdles. First, general, off-the-shelf tools are unlikely to
adequately perform complex, specific tasks, such as
portfolio analysis and selection. Companies will need
to train their own models, a process that will require
substantial time and investment.
Once such software is complete, its output may
be problematic. The risks of bias and lack of
accountability in AI are well known. Finding ways to
validate complex output from generative AI has yet to
see success. Any new tool has to be designed to avoid
violating other actors intellectual property (IP) rights;
and generative AI algorithms may act unpredictably
even illegallyespecially when interacting with other
ones. Finally, so-called hallucinations, or confident
wrong answers, are a worry with any use of generative
AI. These risks mean that financial services companies
must be cautious in how they deploy generative AI.
Financial regulators are certainly wary about how
these tools may be used. Companies are hoping
for guidance, but this will take time. Authorities
acknowledge that they need to study the implications
of generative AI more, and historically they have rarely
approved tools before rollout. Meanwhile, the possible
benefits of any extensive use of generative AI need to
be weighed against regulatory dangers.
Adoption of generative AI is growing in the financial
services sector, but it is so far limited to automation of
low-value activities where its use can be monitored by
humans or would not pose unacceptable risks.
6
MIT Technology Review Insights
02
02
T
o much of the public, the release of ChatGPT in
late 2022 was the first shot in a new
technological revolution. Since then, interest in
generative AI has soared. For example, Google
searches for the term have risen dramatically
in the past year (see Figure 1).
With this interest has come rapid adoption by users
across societies and economies. International Monetary
Fund (IMF) research shows that uptake of ChatGPT
alonejust the most prominent of many generative AI
toolshas been extremely rapid even by the standards
of popular technology adoption (see Figure 2).4
The promise of
generative AI
We tend to overestimate
the impact of any new
technology in the short
run and underestimate it
in the long run.
Chia Hock Lai, Co-Founder, Global Fintech
Institute
Figure 1: The internet discovers a new interest
Searches for the term generative AI by Google users have surged since late 2022, reflecting rapidly growing
interest in the technology.
Note: Interest over time: A value of 100 is the peak popularity for the term. A value of 50 means that the term is half as popular.
Source: Compiled by MIT Technology Review Insights, based on data from Google Trends, 2023.
100
75
50
25
0
Oct. 30, 2022
March 5, 2023
July 9, 2023
Oct. 15-21, 2023
Generative AI 80
Interest over time
7
MIT Technology Review Insights
As with every new technology, a degree of excessive
expectationand fearis inevitably driving the
discussion. Chia Hock Lai, co-founder of the Global
Fintech Institute, says he sees a lot of hype now: We
tend to overestimate the impact of any new technology
in the short run and underestimate it in the long run.
Time for a more measured assessment
Indeed, Gartner reported in August 2023 that
generative AI had peaked in its emerging technologies
hype cycle, after which it would likely take two to five

widespread digitalization and may continue to do so.

In addition, newer companies, notably fintechs, do not

face this issue. The burden of legacy technology will

therefore likely diminish, a process that generative AI, if

anything, can accelerate.

As is the case with any new technology, talent with

expertise specifically in generative AI is in short supply

across the economy. For now, financial services

companies appear to be training staff rather than

bidding to recruit from a sparse specialist pool. That

said, the difficulty in finding AI talent is already starting

to ebb, a process that would mirror those seen with the

rise of cloud and other new technologies.

More difficult to overcome may be weaknesses in

the technology itself and regulatory hurdles to its

rollout for certain tasks. Financial services companies

aiming to benefit from generative AI face several

hurdles. First, general, off-the-shelf tools are unlikely to

adequately perform complex, specific tasks, such as

portfolio analysis and selection. Companies will need

to train their own models, a process that will require

substantial time and investment.

Once such software is complete, its output may

be problematic. The risks of bias and lack of

accountability in AI are well known. Finding ways to

validate complex output from generative AI has yet to

see success. Any new tool has to be designed to avoid

violating other actors intellectual property (IP) rights;

and generative AI algorithms may act unpredictably

even illegallyespecially when interacting with other

ones. Finally, so-called hallucinations, or confident

wrong answers, are a worry with any use of generative

AI. These risks mean that financial services companies

must be cautious in how they deploy generative AI.

Financial regulators are certainly wary about how

these tools may be used. Companies are hoping

for guidance, but this will take time. Authorities

acknowledge that they need to study the implications

of generative AI more, and historically they have rarely

approved tools before rollout. Meanwhile, the possible

benefits of any extensive use of generative AI need to

be weighed against regulatory dangers.

Adoption of generative AI is growing in the financial

services sector, but it is so far limited to automation of

low-value activities where its use can be monitored by

humans or would not pose unacceptable risks.

6

MIT Technology Review Insights

02

T

o much of the public, the release of ChatGPT in

late 2022 was the first shot in a new

technological revolution. Since then, interest in

generative AI has soared. For example, Google

searches for the term have risen dramatically

in the past year (see Figure 1).

With this interest has come rapid adoption by users

across societies and economies. International Monetary

Fund (IMF) research shows that uptake of ChatGPT

alonejust the most prominent of many generative AI

toolshas been extremely rapid even by the standards

of popular technology adoption (see Figure 2).4

The promise of

generative AI

We tend to overestimate

the impact of any new

technology in the short

run and underestimate it

in the long run.

Chia Hock Lai, Co-Founder, Global Fintech

Institute

Figure 1: The internet discovers a new interest

Searches for the term generative AI by Google users have surged since late 2022, reflecting rapidly growing

interest in the technology.

Note: Interest over time: A value of 100 is the peak popularity for the term. A value of 50 means that the term is half as popular.

Source: Compiled by MIT Technology Review Insights, based on data from Google Trends, 2023.

100

75

50

25

0

Oct. 30, 2022

March 5, 2023

July 9, 2023

Oct. 15-21, 2023

Generative AI 80

Interest over time

7

MIT Technology Review Insights

As with every new technology, a degree of excessive

expectationand fearis inevitably driving the

discussion. Chia Hock Lai, co-founder of the Global

Fintech Institute, says he sees a lot of hype now: We

tend to overestimate the impact of any new technology

in the short run and underestimate it in the long run.

Time for a more measured assessment

Indeed, Gartner reported in August 2023 that

generative AI had peaked in its emerging technologies

hype cycle, after which it would likely take two to five