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解决人工智能道德问题有利于企业.pdf
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解决人工智能道德问题有利于企业.pdf
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Why addressing
ethical questions in
AI
will benefit organizations
Why addressing ethical questions in AI will benet organizations
Executive Summary
Every wave of technology development raises its own
set of ethical questions, from unintended and harmful
consequences for users to concerns about technologies
being weaponized. The pace of technological
advancement tends to outstrip the pace of regulatory
and ethical frameworks – a position that AI nds itself
in today. AI has unleashed a range of ethical questions,
from concerns over autonomous vehicles to what
constitutes end-user consent.
To probe these issues, we have conducted a
comprehensive survey of both business executives and
individuals to understand ethics and the transparency
of AI-enabled interactions and what organizations
are doing to address any concerns. We surveyed
1,580 executives in 510 organizations and over 4,400
consumers across countries such as the US, UK, China,
Germany, and France. We found that:
Getting ethics in AI right will benet
organizations and mitigate risks
• AI interactions that consumers and citizens
perceive as ethical build trust and satisfaction:
When consumers and citizens feel an organization
oers ethical AI interactions, over half said that they
would place higher trust in it, share their positive
experience, be more loyal, purchase more, and
advocate for it. Organizations whose AI systems
consumers see as interacting ethically enjoy a
44-point Net Promoter Score (NPS®)
#
advantage
compared to those seen as not using AI ethically.
• AI interactions perceived as unethical can
damage brand reputation: Nearly two in ve
consumers would complain to the company and
demand an explanation if they experienced an
unethical interaction. In the worst case, a third would
stop interacting with that company.
Most organizations have
encountered ethical issues in
AI over the last two to three
years. Consumers seem to
corroborate this nding
• Most executives (77%) are uncertain about the
ethics and the transparency of their AI systems
• Executives in nine out of ten organizations are
aware of at least one instance of the use of AI
systems that resulted in ethical issues (see insert
below for examples of ethical issues)
• Close to half of consumers believe they have felt
the impact of an ethical issue (to probe this matter,
we gave survey respondents specic instances
of unethical practices detailed in the appendix at
the end of the report). This is leading a majority of
consumers (76%) to advocate regulations on the use
of AI: they expect governments, independent bodies
(e.g. IEEE) and regulators to lay down the principles
that dene the just use of AI
• The pressure to implement AI is fueling ethical
issues: Executives identify the pressure to urgently
implement AI as the top reason why ethical issues
arise from the use of AI.
Executives are starting to realize
the importance of ethical AI
and are taking action when
ethical issues are raised
• 51% of executives believe that it is important to
ensure that AI systems are ethical and transparent
• 41% of senior executives report that they have
abandoned an AI system altogether when ethics
concerns were raised; 55% implemented a “watered -
down” version of the system.
2
#
Net Promoter, NPS
®
, and the NPS
®
-related emoticons are registered service marks, and Net Promoter Score and Net Promoter
System are service marks, of Bain & Company, Inc., Satmetrix Systems, Inc. and Fred Reichheld.
What kinds of ethical issues
emerge from the use of AI?
By ethical issues arising from the use of AI, we mean
the interactions that result in outcomes that are
unexplainable, unfair, not transparent and/or biased
against a certain group of users. Examples of AI
interactions that may result in ethical issues include:
• Using AI to screen job applicants that results in a
disproportionate selection of candidates across
gender, ethnicity, age, or other factors
• Using AI for surveillance at the workplace without
the consent of employees
• Using an AI system that is not able to explain how it
arrived at a decision to deny credit or an insurance
claim – or cannot be audited on its decision making
• Collecting and processing healthcare personal data
in AI algorithms without consent
• Discriminatory pricing or availability of products/
services resulting from automated AI decisions.
First steps to proactively
address ethics in AI
Our previous research has established that AI has
signicant potential across industries and functions.
1
By addressing ethics issues upfront, we believe
that organizations stand to gain additional
benets as well as avoid regulatory, legal, and nancial
risks that may result from a market or public backlash
on AI. We have developed a comprehensive approach to
help organizations proactively address ethics questions
in AI. This approach targets three key groups in the
organization:
• General management (CXOs, and business leaders
and those who have questions of ethics and trust in
their remit), who will be responsible for laying the
foundational practices and processes for ethical AI
• Customer-and employee-facing teams (e.g., HR,
marketing, communications, and customer service)
that are responsible for deploying AI ethically for
users, and
• AI, data, operations, and IT teams that design,
develop, and implement AI systems
For CXOs, business leaders and those with a remit for trust and ethics
• Lay down a strong foundation with a strategy and code of conduct for ethical AI
• Develop policies that dene acceptable practices for the workforce
• Build awareness of ethical issues across the organization
• Create ethics governance structures and ensure accountability for AI systems
• Build diverse teams to inculcate sensitivity to ethical issues
For customer-and employee-facing teams
such as HR and marketing
For AI, data, and IT teams
• Ensure that ethics questions are debated from the
design of AI-infused applications by clearly dening the
outcomes and intent of these applications, and
ensuring accountability for them
• Educate and inform users on what building trust in
AI applications means
• Empower users with more control and ability to
seek recourse
• Making AI systems transparent and understandable
• Practice good data management in compliance with
regulations where they exist, and address and monitor
potential biases in data
• Use technology tools to actually build ethics in AI
(bias detection, transparency, explainability,
continuous monitoring of accuracy)
3
Articial intelligence oers a huge opportunity for businesses and the economy, but signicant questions are being
raised about the ethical issues surrounding this technology. To examine these questions more closely, we have
undertaken this research to understand the current relationship between AI applications and their users.
As Figure 1 shows, we examined both sides of the debate – from a business and end-user perspective.
Introduction
4 Why addressing ethical questions in AI will benet organizations4 Why addressing ethical questions in AI will benet organizations
Artificial
intelligence
applications
HR and marketing experts
AI, data teams, and IT experts
Consumers, citizens,
and employees
How to explain AI outcomes to its
users?
How to ensure AI respects data privacy?
How to ensure AI does not
perpetuate bias?
Will AI protect my privacy?
Will AI be transparent and clear?
Will AI be fair and bias-free?
How to make AI explainable?
How to make it interpretable?
What processes and tools are needed
to make AI bias-free?
General Management
What is ethical AI?
Why is it important?
What are the risks of ethical issues
that result from the use of AI?
Source: Capgemini Research Institute analysis.
Figure 1. Scope of our research on ethics in AI
We surveyed over 1,500 industry professionals from 500
organizations; over 4,400 consumers; and conducted
in-depth interviews with over 20 industry executives,
academics, and start-up entrepreneurs (see the research
methodology at the end of the paper for more details).
Through this paper, we want to demonstrate:
1. Why it is important to pursue ethics in AI from a business
perspective. Our analysis shows that individuals (both
consumers and employees) trust organizations that
they perceive to be using AI ethically and are willing to
advocate for them.
2. Why most organizations have encountered ethical issues
in AI over the last two to three years.
3. How organizations can start to address ethics in
AI more proactively. We therefore identied clear and
actionable rst steps while designing, developing, and
using AI applications.
5
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