Policy Frameworks for Generative AI: Mitigating Risks and Maximizing Benefits

Generative AI is a relatively new technology that offers numerous benefits, but also poses significant risks that must be carefully managed to maximize its advantages. These risks include privacy concerns, cybersecurity threats, regulatory compliance issues, and challenges related to intellectual property. Due to its immense power, generative AI's potential for misuse and errors is notably higher compared to other technologies.

A major concern is the potential for misuse, particularly in creating deepfakes, which poses a significant challenge in discerning between reality and fabrication both now and in the future. Without clear policies and ethical guidelines promoting responsible use, misuse could become widespread.

This technology is widely employed in content creation, producing realistic images used for both legitimate and deceptive purposes, contributing to the spread of misinformation.

Issues such as the ownership of AI-generated works and the ethical training of AI models on copyrighted material remain unresolved, lacking a comprehensive framework to address these complexities.

Let’s understand this with an example: how generative poses risk to business owners and what steps they need to take to mitigate risks.

Risks of the generative AI

For example; you own a social media platform and provide users with an AI tool to create content. So they can generate realistic images and videos. While this could be a great move for user engagement and satisfaction, it also raises significant concerns. 

You might know that AI can autonomously generate content, questions arise about who owns the generated content. If AI creates a piece that infringes on copyrights or portrays someone falsely, legal liabilities can emerge for your business.

In addition, AI systems processing vast amounts of user data to personalize content raise privacy concerns. If not properly secured, this data could be vulnerable to breaches, compromising user trust and leading to regulatory issues.

In essence, while generative AI offers many benefits, businesses must proactively manage its risks. 

Factors to consider before creating a policy for generative AI:

Comprehend Generative AI: Make sure you have an understanding of what generative AI is, and what are the applications of generative AI (Cluster 2nd). Ensure that you are accustomed to basic models of generative AI like ChatGPT, DALL-E, and more. 

Evaluate organizational needs:  Assess how your organization intends to use Generative AI, whether for Content creation, data analysis, or something else. 

Research established regulations: Survey already established legal and regulatory rules about generative AI in your industry or jurisdiction. 

Examine potential risk: Identify potential risks associated with the deployment of generative AI in your organization this includes both technical and ethical concerns.

Assess established policies: Before you create something new make sure you know about existing IT and InfoSec policies, This ensures consistency and clarity and avoids any overlapping of the policies.

Purpose: Make sure why you are creating policies, who is it for? And what values and beliefs it should adhere to. You can evaluate these 5 principle questions about AI ethics that can help: 

The five principles of AI ethics answer different questions and focus on different values:

1. Should we use AI for good and not for causing harm? (the principle of beneficence/ non-maleficence)

2. Who should be blamed when AI causes harm? (the principle of accountability)

3. Should we understand what, and why AI does whatever it does? (the principle of transparency)

4. Should AI be fair or non-discriminative? (the principle of fairness)

5. Should AI respect and promote human rights? (the principle of respecting basic human rights)

Drafting Generative AI usage policy

Drafting a thorough policy for generative AI is like creating a legal argument. Both require in-depth details and planning, thoroughness in cases when rules are breached and consideration and anticipation of all scenarios and threats before they arise. 

Primary subjects to include in Policy:

Data Administration

Mention clearly how data will be collected, saved, and used by AI. This will educate them on how AI collects and stores data, Furthermore, it will help them realize what type of data should be used when using AI. It will make private data more secure and prevent it from leaking. 

Ethical concerns

Create guidelines regarding the ethical use of AI, particularly issues like bias and discrimination. And make sure they know how these actions can be detected and what actions will be taken against such actions. 

Adherence to regulations

Lay down laws and regulations that the AI system must follow. This ensures safety regarding data protection and intellectual property. Also, mention the legal consequences of not complying with this. 

Employee training

Elaborate training campaigns that will be placed within the company, to educate employees about data ownership in the context of generative AI, emphasizing data security practices.

Authority

Mention who is responsible for the use and deployment of AI within the organization.

Conclusion

As we discussed what factors to consider when drafting or implementing generative AI policy, but that is not the end. Crafting a generative AI policy is crucial, but it's a starting point, not a finish line. AI is constantly evolving, and so should your policy. Actively monitor legal and technological developments, schedule regular policy reviews, and be prepared for proactive updates. By keeping your policy a living document, you can ensure the safe and ethical use of this powerful technology.