Five reasons to prioritize responsible AI: Your key to success in the age of AI

Part one of a three-part blog series on responsible AI that focuses on “why.” Coming soon: Part two focusing on “who” and part three focusing on “how.”

Good AI is good for business, and importantly, good AI is responsible.

The rise of generative AI has sparked new interest in the potential of artificial intelligence. This surge is due to its promise to make AI accessible to everyone. It has also highlighted the deliberate and inadvertent risks of AI. Generative AI can tackle diverse business challenges but requires careful and ethical use to counter risks and maximize its benefits.

Governments are trying to protect citizens and consumers from dangers such as misinformation, fraud and discrimination through legislation and regulation. But bad AI is bad not only for society but also for businesses. Organizations should do more than react to comply with new rules and legislation. When done well, good AI benefits society through responsible AI practices and serves as an innovation accelerator for business.

Responsible AI involves implementing AI in a way that is transparent, fair, secure, inclusive, accountable and sustainable. Generally, it encompasses these six principles:

• Sharing information about AI systems and outputs transparently, including explainability of how decisions are made with AI.
• Addressing fairness issues like harmful bias and discrimination to promote equality and equity.
• Safeguarding human autonomy, identity and dignity for better safety and security.
• Accommodating a broad group of people with inclusivity.
• Meeting the needs of the present without compromising the needs of future generations through sustainability efforts.
• Acting as a guardian of integrity, with everyone demonstrating personal accountability toward ensuring AI is safe, ethical and secure.

More than half of organizations (55%) say they haven’t fully comprehended the ethical implications of AI, according to Unisys’ “From Barriers to Breakthroughs: Unlocking Growth Opportunities With Cloud-Enabled Innovation” research report. But they must understand and there’s still time to learn. Here are five reasons responsible AI is imperative when introducing the technology into your organization.

Reason #1: Responsible AI is a business strategy

AI and the future of business are frequently discussed together. The technology is even reshaping business strategies. Responsible AI builds trust with customers, stakeholders and the public, which is critical for long-term business success. Responsible AI promotes fairness, inclusiveness and the prevention of harm. By embedding these principles into AI use, your organization can create more equitable and unbiased technologies, which can enhance its reputation and market reach.

C-suite executives are more likely than IT members to say they don’t understand the ethical implications of AI (66% vs. 51%), according to the Unisys research report. But viewing the implications through a business lens can assist with understanding. Once public trust erodes, it’s hard to earn it back. If you don’t implement AI and monitor usage properly, it could harm your reputation, hurt your brand and negatively impact your finances.

Referencing AI use in your ethics guidelines is a fantastic start, something more organizations are doing. They recognize that not stipulating responsible AI measures can leave you vulnerable to security and privacy breaches, exposure of proprietary information and other detrimental issues for the business.

Reason #2: Responsible AI minimizes risks

Misuse of AI in a business setting is usually inadvertent. Generative AI has made it easier to infringe on copyright, disclose proprietary information and create misinformation. Spending time to understand responsible AI principles, how they apply to your business practices and processes, and setting the guidelines and policies for your business minimizes the financial and reputation risks that can come with the misuse of AI.

Generative AI carries risks when used without proper care. These risks include misinformation, where someone has purposefully fed false information to AI models, and disinformation, where someone has inadvertently given the models false information. Both can be equally damaging to the people or organizations affected as they can result in the spread of false narratives.

Reason #3: Responsible AI makes it easier to satisfy government regulations

Business leaders and governments are concerned about the misuse of generative AI. They’re demonstrating this concern and determination to protect the public by enacting regulations that aim to protect the public’s rights and counter the potential harm unchecked AI can have on society.

Examples of these regulations include the European Union AI Act, which contains stringent restrictions on AI use, and in the U.S., recently approved legislation in Colorado, the Utah Artificial Intelligence Policy Act and a Florida law requiring disclaimers on AI political ads. Keeping up with the myriad of local, national and global regulations can be challenging, but not keeping up with them can have serious financial consequences.

Reason #4 – Responsible AI helps maintain positive relationships

Goodwill goes a long way in any industry – with customers, partners, prospects, competitors and the general public. Building trust is essential to any successful business and the primary goal of responsible AI is to foster trust in the use of technology. One way to do this is by disclosing when and how AI is being used.

The foundation of AI is data – what data is used and how it is used. All data and information used for AI must be kept safe, secure, private and confidential, as appropriate. In addition, the data should be used ethically and responsibly. When generative AI was first growing in popularity, there were instances where a company’s proprietary code was exposed through the use of AI models. While such instances are less likely to occur now because organizations have become more educated on the risks, caution should still be a priority. And technology providers have addressed this concern, too.

You should also look out for others. While you may shelter your own data from such models, you may inadvertently gain access to other organizations’ proprietary information through such models, leading to license and copyright infringement issues and roadblocks to future business relationships.

Reason #5 – Responsible AI enables innovation

This reason may seem counterintuitive. After all, doesn’t adding more requirements or limits to a scenario slow everything down? But rather than inhibiting innovation, responsible AI actually enables more of it. If you infuse responsible principles into your AI adoption from the beginning of your journey, you will open doors and be much more successful with your business initiatives.

That’s because responsible AI means you’re thoughtfully considering principles like sustainability and diversity. You’re positioning your innovation in a broader context. Acting responsibly from the beginning could also prevent delays caused by later realizing your data is biased and you have to redo the entire process. There’s a higher probability of success if you consider everything at the outset.

Implementing responsible AI at an enterprise level

Establishing strong governance and accountability mechanisms for AI initiatives ensures that AI use is reliable, safe and respectful of privacy. Putting responsible AI into practice at an enterprise scale requires a comprehensive approach involving collaboration between IT, legal, procurement, business units and others. By prioritizing responsible AI, organizations can safeguard operations and drive growth and innovation in a sustainable and ethical manner.

Organizations need to assess existing policies, establish new guidelines and extend responsible practices to the extended ecosystem of vendors and partners. This structured approach can help your organization maintain control over its AI use and align it with ethical principles. In a future blog post, we'll explore how to operationalize responsible AI principles across an organization, including frameworks and best practices for effective enterprise-wide AI governance and risk mitigation.

In the meantime, you can identify opportunities for AI in your organization and explore how AI solutions from Unisys can help you adopt AI responsibly.

Learn more