Generative AI Ethics: Balancing Innovation with Responsibility

Ethics of generative AI: what to know in 2024

Generative AI programs like OpenAI’s ChatGPT, Google's Gemini, and Microsoft’s Copilot are great tools for increasing your productivity or innovating new solutions at scale. Generative AI refers to the subset of artificial intelligence tools that an individual or business can use to generate content or information. While other types of AI might focus on analyzing or interpreting data, generative AI functions to produce new outputs that, in some cases, might resemble the original content, or information used to train the GenAI model. 

Read more: What Is Generative AI? Definition, Applications, and Impact

As society rapidly integrates generative AI into many personal and professional tasks, developers, businesses, lawmakers, AI ethicists, and general users have a stake in what is considered ethical or unethical in using generative AI. Given some of the risks inherent in AI and the fact that regulations and governance of AI are still being developed, there is some urgency around establishing these standards. 

For example, in the realm of content creation, AI-generated text, images, and videos make possible the spread of misinformation at scale, given that it’s getting more difficult to tell human-generated content from AI-generated content. Clear ethical guidelines around AI-generated content could help reduce the spread of misinformation.

Here are some questions to consider around the ethics of generative AI:

• How do we define ethical or unethical use of generative AI?

• What tangible benefits are involved in ethical GenAI use?

• What are the risks of unethical GenAI use?

• How do we ensure that we are using GenAI ethically, even as this technology keeps evolving?

Keep reading to explore the ethical use of GenAI, the benefits of these practices, risks associated with GenAI, and how to set up your business for ethical AI use.  

Learn how Coursera CEO Jeff Maggioncalda leverages generative AI models, from his set-up and model choices to hands-on prompting examples, in his three-hour course Use Generative AI as Your Thought Partner.

How do you use GenAI ethically?

In general, using GenAI ethically means designing, managing, and using these tools responsibly while avoiding harming others. The ethical use of generative AI has several components that you’ll need to consider, whether you’re a developer designing or improving AI tools, a business leader integrating GenAI into business practices, or an individual user looking to increase productivity. 

The following components can apply to many different generative AI use cases: 

Professional and creative integrity

When using GenAI for academic, professional, or creative purposes, it’s essential to acknowledge how you use AI to produce work. Doing so can help ‌establish trust and credibility in your field. 

Respecting intellectual property

When using GenAI tools, be sure to comply with copyright laws and avoid plagiarizing the original work of others. In addition, avoid inputting copyrighted material to GenAI tools to generate outputs. If you do reference work by others, be sure to provide the proper attributions.  

Data privacy 

GenAI tools are trained on large and diverse data sets. In addition, they can process a lot of data in a short period of time. While these capabilities make GenAI powerful tools for generating useful outputs, it’s essential to protect the privacy of individuals whose data might be involved in GenAI training. 

Transparency

Transparency in the world of GenAI works alongside data privacy, professional and creative integrity, and respecting intellectual property. You should communicate openly with stakeholders, users, or collaborators regarding how AI-generated content is produced, the sources of data, and documenting how a GenAI tool works. Transparency can also refer to communication across industries and sectors to share best practices and collaborate on creating ethical AI guidelines. 

Eliminating bias 

When using GenAI to create content, it’s important to mitigate potential bias in the outputs. Bias in GenAI outputs can occur when the data a model is trained on is incomplete, limited, or skewed. Biased outputs might represent the experiences and views of only a narrow demographic or contain content that some demographics might find offensive. 

You can mitigate bias by training a model with comprehensive data that comes from diverse sources, adopting a system to re-train models on an iterative basis, and once again being transparent with the sources models are trained on. 

Third-party fact-checking

Third-party fact-checking refers to the process of verifying the accuracy and credibility of AI-generated content. While GenAI can often produce elegant outputs that closely resemble human communication, the outputs may not always be based on factual information. It’s up to users to consult reputable sources of information or subject-matter experts when evaluating the quality and accuracy of a GenAI output. 

Empowering and reskilling the workforce

Given that GenAI tools can automate many work-related tasks, there are some jobs that might become obsolete as companies adopt GenAI. This presents an ethical concern, as members of the workforce face unemployment or job displacement. Company leaders can, instead, work to empower and reskill employees whose jobs are affected by AI or even support employees in transitioning to a new role or industry.  

Read more: AI Ethics: What it Is and Why it Matters 

Watch this video for more ideas about the importance of ethical AI practices. 

Benefits of the ethical use of AI

Using generative AI ethically offers several benefits to organizations, industries, individual users, and society at large. As a leader within an organization or individual GenAI user, your responsible use of these tools can help you garner trust and build a positive reputation in your field. You can also create content that promotes fairness and inclusivity while exploring your creative potential. 

Responsible and ethical use of GenAI can also lead to more innovation that makes a positive impact on the world. For example, nonprofit and charitable organizations can use GenAI to improve their operational efficiency by automating processes, enabling humans to focus more on strategy and providing more services.

Explore more examples of how you can use AI to create a better world in DeepLearning’s AI for Good Specialization.

Generative AI risks 

Using GenAI ethically can spark creativity and innovation. However, it comes with inherent risks that you’ll need to understand. Understanding these can strengthen your commitment to ethical AI use and make it easier to develop a comprehensive risk management plan.

Some of the most common GenAI risks include (but aren’t limited to): 

• Hallucinations: incorrect or misleading AI outputs that result from limited or biased data that the model was trained on. Using hallucinatory outputs without fact-checking them could lead to unintended consequences if people take action based on the inaccuracies they encounter. 

• Deepfakes: audio, images, or video that appear to be real, but have been manipulated by AI. Deepfakes can be used maliciously, such as to impersonate politicians and sway elections.

• Job displacement: automation and efficiency of GenAI may make some job roles or industries obsolete, thus affecting members of the workforce and the economy at large.

How to use GenAI ethically in your business

Knowing the ethics, benefits, and risks of generative AI is crucial for businesses to harness its full potential. Here’s how you can establish responsible practices in your business: 

1. Identify what you’re using it for. 

Start the GenAI implementation process by defining which AI tools your business will use and how it will use them. Uses might include creating content, developing products, or automating customer service. Knowing your business’s use cases will help ‌align them with ethical considerations.

2. Set quality standards. 

Define the criteria for evaluating the quality of GenAI outputs. Criteria could include accuracy, diversity and inclusion, adherence to a particular style or brand voice, and fairness. Schedule time to monitor outputs and retrain AI tools to improve their performance. 

3. Keep humans at the center of GenAI.

Emphasize the importance of augmenting rather than replacing human capabilities with the use of GenAI. Make sure humans make the decisions for every initiative, including AI-powered content or data. 

If you’re a leader within your organization, you might consider appointing an AI ethics specialist to help guide how the organization uses GenAI and to provide oversight on AI’s ethical use. 

4. Create organization-wide AI policies.  

Develop comprehensive GenAI policies and guidelines that cover all functions and departments within your organization. The policies should address ethical considerations, data privacy, transparency, compliance, how to mitigate bias and other risks, and professional integrity. 

5. Create a public-facing statement on GenAI use.

Communicate your organization’s commitment to the ethical use of generative AI through a public-facing document. This document should express your organization’s AI principles, values, and practices, and reassure customers, stakeholders, and the general public of your organization’s AI ethics. 

6. Review GenAI policies regularly.

Regularly review and update your organization’s policies on GenAI use to make sure they reflect the latest ethical standards, regulatory requirements, and technological advancements. 

7. Engage with AI ethics communities. 

Participate in AI ethics forums, communities, and initiatives to stay informed about emerging ethical practices. Collaborate with AI ethics researchers, industry experts, and technologists to contribute to the future of GenAI use.  

Explore generative AI with Coursera

Taking online courses is a great way to gain a deeper understanding of generative AI and the ethics around its use. Coursera offers several options that provide a GenAI overview and insights into the ethics of AI:

The Google AI Essentials Course covers writing effective prompts, developing content, avoiding harmful AI use, and staying up-to-date in an AI world. This program takes about nine hours to complete. 

To focus specifically on the ethics of GenAI, consider enrolling in IBM’s five-hour course, Generative AI: Impact, Considerations, and Ethical Issues. This program covers GenAI’s limitations, ethical issues, concerns, economic and social impact, and more. 

To dive deeper into AI, consider enrolling in DeepLearning.AI’s AI for Good Specialization. You can complete this program in about a month and learn how to develop AI projects for air quality, wind energy, and disaster management while exploring real-world case studies related to these issues.