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Demystifying Responsible AI For Business Leaders

Artificial intelligence is changing the way companies conduct business. Understanding how to use AI responsibly will set them up for long-term success.

Sean Richards

December 26, 2023

4 Min Read
AI (Artificial Intelligence) concept.
chombosan via Alamy Stock

In a recent survey of business leaders, nearly 90% agreed that clear and transparent guidelines around the ethical use of AI are important. But despite this strongly held stance, only a few respondents noted that they have a solid understanding of what responsible AI usage actually looks like.

This vast disparity clearly points to the need for a broad discussion about how, when, and why companies use AI. Customers who rely on your goods and/or services shouldn’t have to worry that the company that produces the products they use is harnessing any new technology in a way that might be considered unethical or irresponsible.

For IT professionals, this poses a challenge, as AI has advanced more rapidly than any regulation that could limit its use. Those rules are most certainly coming, and it’s important for leaders in IT to “future-proof” AI implementation so that vast changes aren’t needed if a new regulation is adopted. It’s a delicate balance, but with a bit of planning and some clear goals, it’s possible to leverage the incredible power of artificial intelligence without any major risks.

Striking the Balance

For technology professionals, there are three main ethical concerns regarding AI and its various implementations: ownership, privacy, and accuracy.

Related:ChatGPT: Benefits, Drawbacks, and Ethical Considerations for IT Organizations

1. Ownership

This applies primarily to companies wishing to use AI tools to make their employees' lives a little easier or give them a creative edge in the marketplace.

Freely available AI tools are can generate text content and even code on a large scale, but if an AI tool is trained on copyrighted material, there’s always the risk that any text produced by that AI will include parts of the original copyrighted work. This is true for everything from fiction writing to coding iOS apps, so it’s important to understand the implications. When utilizing an AI tool to produce these types of content, it’s vital to ensure that no copyrighted material is included in the final product.

It’s not as simple as merely asking a generative AI tool to create something from scratch -- or even help to flesh out written content or finish some code -- so ensure that whichever form of artificial intelligence you choose to deploy or use was trained on data that is copyright free or part of the public domain.

Any text, code, or art that is generated by AI should be treated with utmost care and understanding. Without doing so, you risk the integrity of the final product.

2. Privacy

For companies that will be implementing their own AI tools, or utilizing third-party AI with custom data sets that may include company or user information, privacy should always be top of mind.

Related:The Evolving Ethics of AI: What Every Tech Leader Needs to Know

Because AI systems are still beholden to the same privacy laws and regulations as any other software framework, it’s vital that IT leaders ensure their firm demonstrates a clear, deep understanding of how the data is managed, stored, and used. This should be a transparent process, offering the end user a clear and straightforward understanding of how their data is collected, used, and where/if it’ll be stored.

If user data is being utilized to further train an AI or even build a new model, disclosure is a must. Depending on the locality, there may or may not be rules in place already that demand these types of disclosures, but it’s a safe bet that they will become universal in the near future.

3. Accuracy

It seems as though many in the business world see AI as an unfailing entity that, drawing on the vast resources of the data sets it is trained on, can do no wrong. IT professionals know that no machine is infallible, and AI is no exception.

Artificial intelligence is just as susceptible to errors as a human -- and in some cases, even more so. Because AI tools are trained on data produced by (you guessed it) humans, it’s equally adept at mixing things up, misremembering key facts, and even being flat-out wrong. Blindly relying on AI to get your content right, create clean code, or edit an existing piece of work is a recipe for disaster.

Related:Data Leaders Say ‘AI Paralysis’ Stifling Adoption: Study

AI-written content or code should always be scoured with a fine-toothed comb for errors both factual and grammatical, and no piece of artificial intelligence-derived content should ever see the light of day until it has gone through a robust editing and verification process.

Risks and Rewards

For many IT leaders, the risk of AI creation is worth the reward when doing so ethically and mindfully.

A recent IBM study conducted across 3,000 C-suites globally found that using AI is no longer a point of hesitation but a must-have. If organizations begin by leveraging AI in ethical, productive ways, including addressing ongoing regulatory developments, optimal usage of the technology will be easier in the long run because the right standards have been set up from the start. This ensures that responsible AI implementation is in place for the long haul and business leaders will reap the benefits.

Above all, recognize that generative AI is not one of those flash-in-the-pan trends that will disappear just as fast as it arrives; it’s an emerging technology, and we’re really just beginning to see what it is capable of. Companies that learn to harness it now will be set up to thrive in the future, while those who ignore it will likely regret it. Being on the right side of history means doing your homework.

About the Author(s)

Sean Richards

Head of Quality & Growth, Vincit

Sean Richards is Head of Quality & Growth at Vincit, a leading software development and design company. Prior to his current role, he also served Vincit as Head of Operations in Arizona, and Head of Marketing & Customer Experience.

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