Written by Coursera Staff • Updated on
AI ethics in technological advancements can help foster a world with less bias and more fairness. Here’s what it is and why it matters.
As artificial intelligence (AI) becomes increasingly important to society, experts in the field have identified a need for ethical boundaries when it comes to creating and implementing new AI tools. Although there's currently no wide-scale governing body to write and enforce these rules, many technology companies have adopted their own version of AI ethics or an AI code of conduct.
AI ethics are the moral principles that companies use to guide responsible and fair development and use of AI. In this article, we'll explore what ethics in AI are, why they matter, and some challenges and benefits of developing an AI code of conduct.
What are AI ethics?
AI ethics are the set of guiding principles that stakeholders (from engineers to government officials) use to ensure artificial intelligence technology is developed and used responsibly. This means taking a safe, secure, humane, and environmentally friendly approach to AI.
A strong AI code of ethics can include avoiding bias, ensuring privacy of users and their data, and mitigating environmental risks. Codes of ethics in companies and government-led regulatory frameworks are two main ways that AI ethics can be implemented. By covering global and national ethical AI issues, and laying the policy groundwork for ethical AI in companies, both approaches help regulate AI technology.
More broadly, discussion around AI ethics has progressed from being centered around academic research and non-profit organizations. Today, big tech companies like IBM, Google, and Meta have assembled teams to tackle ethical issues that arise from collecting massive amounts of data. At the same time, government and intergovernmental entities have begun to devise regulations and ethics policy based on academic research.
Stakeholders in AI ethics
Developing ethical principles for responsible AI use and development requires industry actors to work together. Stakeholders must examine how social, economic, and political issues intersect with AI, and determine how machines and humans can coexist harmoniously.
Each of these actors play an important role in ensuring less bias and risk for AI technologies.
Academics: Researchers and professors are responsible for developing theory-based statistics, research, and ideas that can support governments, corporations, and non-profit organizations.
Government: Agencies and committees within a government can help facilitate AI ethics in a nation. A good example of this is the Preparing for the Future of Artificial Intelligence report that was developed by the National Science and Technology Council (NSTC) in 2016, which outlines AI and its relationship to public outreach, regulation, governance, economy, and security.
Intergovernmental entities: Entities like the United Nations and the World Bank are responsible for raising awareness and drafting agreements for AI ethics globally. For example, UNESCO’s 193 member states adopted the first ever global agreement on the Ethics of AI in November 2021 to promote human rights and dignity.
Non-profit organizations: Non-profit organizations like Black in AI and Queer in AI help diverse groups gain representation within AI technology. The Future of Life Institute created 23 guidelines that are now the Asilomar AI Principles, which outline specific risks, challenges, outcomes for AI technologies.
Private companies: Executives at Google, Meta, and other tech companies, as well as banking, consulting, health care, and other industries within the private sector that uses AI technology, are responsible for creating ethics teams and codes of conduct. This often creates a standard for companies to follow suit.
Why are AI ethics important?
AI ethics are important because AI technology is meant to augment or replace human intelligence—but when technology is designed to replicate human life, the same issues that can cloud human judgment can seep into the technology.
AI projects built on biased or inaccurate data can have harmful consequences, particularly for underrepresented or marginalized groups and individuals. Further, if AI algorithms and machine learning models are built too hastily, then it can become unmanageable for engineers and product managers to correct learned biases. It's easier to incorporate a code of ethics during the development process to mitigate any future risks.
AI ethics in film and TV
Science fiction—in books, film, and television—has toyed with the notion of ethics in artificial intelligence for a while. In Spike Jonze’s 2013 film Her, a computer user falls in love with his operating system because of her seductive voice. It’s entertaining to imagine the ways in which machines could influence human lives and push the boundaries of “love”, but it also highlights the need for thoughtfulness around these developing systems.
Examples of AI ethics
It may be easiest to illustrate the ethics of artificial intelligence with real-life examples. In December 2022, the app Lensa AI used artificial intelligence to generate cool, cartoon-looking profile photos from people’s regular images. From an ethical standpoint, some people criticized the app for not giving credit or enough money to artists who created the original digital art the AI was trained on [1]. According to The Washington Post, Lensa was being trained on billions of photographs sourced from the internet without consent [2].
Another example is the AI model ChatGPT, which enables users to interact with it by asking questions. ChatGPT scours the internet for data and answers with a poem, Python code, or a proposal. One ethical dilemma is that people are using ChatGPT to win coding contests or write essays. It also raises similar questions to Lensa, but with text rather than images.
These are just two popular examples of AI ethics. As AI has grown in recent years, influencing nearly every industry and having huge positive impact on industries like health care, the topic of AI ethics has become even more salient. How do we ensure bias-free AI? What can be done to mitigate risks in the future? There are many potential solutions, but stakeholders must act responsibly and collaboratively in order to create positive outcomes across the globe.
Ethical challenges of AI
There are plenty of real-life challenges that can help illustrate AI ethics. Here are just a few.
AI and bias
If AI doesn’t collect data that accurately represents the population, their decisions might be susceptible to bias. In 2018, Amazon was under fire for its AI recruiting tool that downgraded resumes that featured “women” (such as “Women’s International Business Society”) in it [3]. In essence, the AI tool discriminated against women and caused legal risk for the tech giant.
AI and privacy
As mentioned earlier with the Lensa AI example, AI relies on data pulled from internet searches, social media photos and comments, online purchases, and more. While this helps to personalize the customer experience, there are questions around the apparent lack of true consent for these companies to access our personal information.
AI and the environment
Some AI models are large and require significant amounts of energy to train on data. While research is being done to devise methods for energy-efficient AI, more could be done to incorporate environmental ethical concerns into AI-related policies.
How to create more ethical AI
Creating more ethical AI requires a close look at the ethical implications of policy, education, and technology. Regulatory frameworks can ensure that technologies benefit society rather than harm it. Globally, governments are beginning to enforce policies for ethical AI, including how companies should deal with legal issues if bias or other harm arises.
Anyone who encounters AI should understand the risks and potential negative impact of AI that is unethical or fake. The creation and dissemination of accessible resources can mitigate these types of risks.
It may seem counterintuitive to use technology to detect unethical behavior in other forms of technology, but AI tools can be used to determine whether video, audio, or text (hate speech on Facebook, for example) is fake or not. These tools can detect unethical data sources and bias better and more efficiently than humans.
Keep learning
The ultimate question for our society to answer is, how do we control machines that are more intelligent than we are? Lund University’s explores the ethical and societal impact of AI technologies. Ranging from algorithmic bias and surveillance, to AI in democratic vs. authoritarian regimes, you’ll learn about AI ethics and why it matters in our society.
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