AI guidelines to encourage responsible use

AI is everywhere

Artificial intelligence (AI) is significantly transforming the global technology landscape. ChatGPT, a free generative AI chatbot launched in 2022, cemented AI’s prevalence, amassing more than one million users in the initial week of its launch. The AI market is predicted to grow from $86.9 billion in 2022 to nearly $410 billion by 2027, while generative AI adoption is expected to grow by 35%.¹ Amid such a rapid expansion, it’s recommended that industries utilizing AI establish responsible use guidelines rooted in ethics. A definitive and regulated framework of ethical technology standards is crucial to protecting sensitive data, intellectual property, and ensuring the responsible development of AI moving forward.

In this article, we’ll explore some key considerations for your enterprise AI strategy, particularly regarding AI guidelines.

The dangers of irresponsible use

Concerns about AI ethics continue to rise with its growing presence. The lack of explainability in large language models (LLMs), like those used in popular generative AI platforms, presents a challenge to adoption at the enterprise level, as it creates trust and safety concerns. We’ll explore some of the possible implications of poor AI use below.

One of the most prominent ways irresponsible AI use can negatively impact your business is by damaging your brand’s reputation and trustworthiness. If AI is used to make a decision, write a communication, or provide guidance, it must be in a way that’s both explainable and trustworthy. If not, you run the risk of bias interference. AI bias refers to a system where AI can reflect the biases and prejudices existing in its development environment, often because of the data it was trained on. If the dataset the AI system was trained on contained biases or didn’t account for certain populations, the AI will likely adopt these biases. Understanding and mitigating AI bias is critical, as these biases can interfere with people’s lives and do notable damage not just to their end users, but also to the organizations responsible for their use. Ensuring your brand, data, and decisions are trustworthy is crucial, and this can only be achieved through responsible AI use.

Another danger of irresponsible AI use is plagiarism. Because AI systems are trained on datasets from other sources, and aren’t necessarily trained to create unique prose, answers from AI can be plagiarized from other sources and not appropriately cited, if at all. Failing to verify that AI-generated content isn’t plagiarized can pose both brand and legal challenges.

Beyond brand trust and authenticity, unregulated AI use can pose serious cybersecurity risks. For example, the rise of deepfakes, highly realistic fake video or audio recordings used for misinformation, can trick individuals into believing they’re interacting with a trusted entity. This can result in financial losses, data breaches, and legal trouble, among others. Additionally, providing open-source AI platforms with confidential or proprietary information can expose your organization to serious threats. Ensuring your teams are educated on how to identify, respond to, and use AI will be a key component of your strategy.

Key considerations for your AI guidelines

AI isn’t going anywhere, and the market continues to grow. Because of this, and because of its considerable value in streamlining operations and helping you work smarter, adoption is going to grow too. But to embrace AI without putting yourself and your organization at risk, it’s important to have a set of guidelines to shape your AI journey.

Here are some of the most important.

1. Transparency: Maintain clarity about how AI systems work, the data they use, and the rationale behind their decisions to build trust and accountability.
2. Accountability: Define clear lines of accountability for AI system’s behavior, including mechanisms for reporting and addressing negative impacts and educating users about their responsibilities with respect to AI outcomes.
3. Reliability and safety: Ensure AI systems are reliable and safe, functioning as intended under various conditions, and that they include fail-safes to prevent harm.
4. Privacy and security: Implement strong privacy protections and security protocols to secure against the misuse or sharing of any personal or sensitive information.
5. Fairness and non-discrimination: Design AI systems to be inclusive, considering diverse user needs and avoiding biases that could lead to exclusion or discrimination.
6. Human oversight: Establish mechanisms for meaningful human oversight to monitor and evaluate AI decisions, including enabling human intervention in real-time.
7. Respect for human autonomy: Ensure that AI systems support and enhance human decision-making without allowing an AI system to make critical decisions without human judgement.
8. Auditability: Implement regular audits of AI systems to assess their performance and compliance with regulations and ethical standards. Enforce the ability for the AI solution to explain to a human user how it made a decision and provide detail on data and decision-making frameworks that were used.

Keeping these guidelines top of mind as you roll out AI on an enterprise level will help keep yourself, your data, and your company safe.

The path toward transparent, governable AI

The key to successful AI adoption is being intentional and structured in the way you develop and use it. Keeping both short- and long-term goals in mind as you build your strategy can help you identify the most important areas you’ll need to monitor, and keeping communication open amongst those overseeing your AI systems and those using them will be critical. Building a framework of guidelines will hold your teams accountable for responsible use, helping to protect your data and your brand from unwanted interference. With a solid understanding of responsible use, you can harness the transformative power of AI all while staying protected against rising threats.