The applications of Artificial Intelligence (AI) are constantly expanding, opening up new possibilities in workflows, processes, and technological solutions. In a digitally connected future, where machines and humans work together for remarkably impressive results, companies that successfully adopt ethical AI will have an advantage.

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Five Ways to Build Ethics and Trust in AI
The applications of Artificial Intelligence (AI) are constantly expanding, opening up new
possibilities in workflows, processes, and technological solutions. In a digitally connected future,
where machines and humans work together for remarkably impressive results, companies that
successfully adopt ethical AI will have an advantage.
As AI becomes more pervasive in people’s daily lives, the conversation shifts from technological
advancement to the ramifications of using AI. When it comes to AI applications, security, privacy,
ethics and bias are becoming increasingly important. Artificial intelligence (AI) helps decision-
making, posing risks such as mimicking or amplifying human biases. As a result, it is critical for
businesses to ensure that AI systems are transparent and fair
However, how does one ensure that AI is aligned with their business models and fundamental values
while leveraging it to achieve the best possible results? How do they create trustworthy AI systems?
Designing AI systems that are responsible
The ethics of high-stakes AI applications have become a controversial issue. Even though AI
technologies help with decision-making they come with several risks such as simulating human
biases through the ML programming. Due to historical human biases, even when datasets reflect
adequate demographic representations, AI output may still present compromised results.
Also Read: Three Enterprise AI Trends in 2022
While ethics in AI is still a work in progress, responsible AI entails creating systems that are bound by
fundamental guidelines that discriminate between permissible and illicit uses of AI. AI systems must
be transparent, human-centric, interpretable and socially helpful in order to be considered as
responsible AI.
By Prangya Pandab - March 30, 2022

2. 3/31/22, 6:06 PM Five Ways to Build Ethics and Trust in AI
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Here are five steps to developing trustworthy AI that organizations can adopt.
Begin at the very top
Most top-level management are aware of common ethical or compliance risks in their industry, but
many are still unaware of how AI is built and deployed within their companies. Leaders must be
educated on the principles of trustworthy AI so that they can take a clear stand on ethics and AI
while also ensuring that it complies with applicable laws and regulations.
Perform risk assessments
The risks must be understood. Because AI is an emerging technology, its regulation and standards
are yet undefined, and the threats are difficult to identify. To map high-risk operations and prepare
mitigation, a risk assessment framework will be crucial.
Determine the baseline
The processes for trustworthy AI should be integrated into the management system of the company.
Policies must be updated to communicate the company’s expectations for preventing AI solutions
from having a negative impact on human rights and to assist in the resolution of any issues that
arise. A reliable AI ethics and compliance policy will require a mix of non-technical and technical
safeguards.
Drive company-wide awareness of AI and ethics
Companies must educate their employees about the legal, societal, and ethical implications of
collaborating with artificial intelligence. The risks associated with AI, as well as any business
strategies for minimizing these risks, should be explained. Rather than focusing on compliance rules,
workshops on ethics and values will be required to train a multidisciplinary workforce on trustworthy
AI.
Bring Third Parties on Board
Companies rarely handle the development of AI-integrated products and services on their own. They
should seek reciprocal commitments from third parties involved in AI development to ensure that the
technology is reliable and created in accordance with the business standards. During the
development of AI solutions, supplier audit procedures will need to be broadened to include an
assessment of how suppliers manage potential detrimental human rights implications.
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Prangya Pandab
Prangya Pandab is an Associate Editor with OnDot Media. She is a seasoned journalist with almost seven years of experience in the
business news sector. Before joining ODM, she was a journalist with CNBC-TV18 for four years. She also had a brief stint with an
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infrastructure finance company working for their communications and branding vertical.
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