AI Ethics: What is AI, why is it important, and more?

Important points

AI ethics are moral principles that guide companies toward the responsible and fair development and use of AI and AI-powered tools.

• AI ethics often aims to reduce or eliminate bias, preserve privacy, consider potential environmental impacts, and provide a framework for responsible implementation.

• Establishing AI ethics requires collaboration between a variety of stakeholders, including researchers and academics, government agencies and commissions, intergovernmental organizations, nonprofit organizations, and private companies.

Learn what ethics in AI is, why it matters, and the challenges and benefits of developing a code of conduct for AI. Then, if you want to learn more about AI ethics, consider taking IBM’s Generative AI Fundamentals Specialization. In this 5-course series, you will have the opportunity to explore the ethical issues of AI and responsible use of AI.

What is AI ethics?

AI Ethics is a set of guidelines used by stakeholders, from engineers to government officials, to ensure that artificial intelligence technologies are developed and used responsibly. This means taking a safe, secure, humane, and environmentally friendly approach to AI.

As artificial intelligence (AI) becomes increasingly important to society, experts in the field recognize the need for ethical boundaries when creating and implementing new AI tools. Although there is currently no broad governing body creating and enforcing these rules, many technology companies have adopted their own versions of AI ethics or AI codes of conduct.

A strong code of ethics for AI includes avoiding bias, ensuring the privacy of users and their data, and mitigating environmental risks. Corporate ethics codes and government regulatory frameworks are the two main ways to implement AI ethics. Both approaches can help regulate AI technologies by covering global and national ethical AI issues and laying the policy foundation for ethical AI in businesses.

More broadly, the debate around AI ethics has evolved from a focus on academic research and nonprofit organizations. Big technology companies like IBM, Google, and Meta are now forming teams to address the ethical issues that arise from collecting large amounts of data. At the same time, governments and intergovernmental organizations are beginning to devise regulatory and ethical policies based on academic research.

AI Ethics and Governance: AI Ethics Stakeholders

Designing ethical principles for the responsible use and development of AI requires collaboration between industry stakeholders, business leaders, and government representatives. Stakeholders must consider how social, economic, and political issues intersect with AI and determine how machines and humans can coexist harmoniously by limiting potential risks and unintended consequences.

Each of these stakeholders plays a critical role in ensuring that bias and risk to AI technology is reduced.

• Scholar: Researchers and professors are responsible for developing theory-based statistics, research, and ideas that can support governments, businesses, and nonprofit organizations.

• government: Agencies and committees within the government can help promote AI ethics in the nation. A great example of this is the “Preparing for the Future of Artificial Intelligence” report produced by the National Science and Technology Council (NSTC) in 2016. [1]. An overview of AI and its relationship to social engagement, regulation, governance, economics, and security.

• Intergovernmental organizations: Organizations such as the United Nations and the World Bank are responsible for raising awareness and drafting agreements on 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. [2].

• Non-profit organization: Nonprofit organizations like Black in AI and Queer in AI are helping diverse groups gain representation within AI technology. The Future of Life Institute created 23 guidelines, now the Asilomar AI Principles, that outline the specific risks, challenges, and outcomes of AI technologies.

• Private company: Executives at Google, Meta, and other technology companies, banks, consulting, healthcare, and other private sectors that use AI technology are responsible for creating ethics teams and codes of conduct. This often sets standards for companies to follow.

Why AI ethics matters

AI ethics are important because AI technologies are intended to augment or replace human intelligence, but the same issues that can cloud human judgment can permeate the technology if it is designed to replicate human life.

AI projects built on biased or inaccurate data can have harmful consequences, especially for underrepresented and marginalized groups and individuals. Additionally, building AI algorithms and machine learning models too quickly can leave engineers and product managers unable to correct for learned biases. To reduce future risks, it is easier to incorporate a code of ethics during the development process.

Examples of concerns about AI

It may be easiest to explain the ethics of artificial intelligence with a real-life example. In December 2022, the app Lensa AI used artificial intelligence to generate cool, cartoon-like profile pictures from people’s regular images. From an ethical standpoint, some criticized the app for not giving credit or enough money to the artists who created the original digital art on which the AI ​​was trained. [3]. According to the Washington Post, Rensa was trained using billions of photos obtained from the Internet without her consent. [4].

Another example is ChatGPT, an AI model that allows users to create original content by asking questions. ChatGPT is trained with data from the internet and can answer questions in a variety of ways, including poetry, Python code, and suggestions. One of the ethical dilemmas is that people are using ChatGPT to win coding contests or write essays. This poses a similar question for Lensa, but with text instead of images.

These are just two common examples of AI ethics. The topic of AI ethics has become even more prominent as AI has grown in recent years, impacting nearly every industry and having a huge positive impact on industries such as healthcare. How can we ensure unbiased AI? What can we do to reduce future risks? There are many possible solutions, but to ensure positive outcomes around the world, stakeholders must act responsibly and collaboratively.

read more: Generative AI Ethics: AI Risks, Benefits, and Best Practices

Ethics of AI: Possible issues

There are many real-world challenges that help explain the ethics of AI. Here we will introduce just a few.

1. AI and bias

If AI does not collect data that accurately represents the population, its decisions may be susceptible to historical bias. In 2018, Amazon came under fire for an AI recruiting tool that downgraded resumes that included the word “female,” such as “Women’s International Business Association.” [5]. In essence, this AI tool discriminated against women and created legal risks for the tech giant.

2. AI and privacy

As mentioned earlier in the Lensa AI example, AI relies on data obtained from internet searches, social media photos and comments, online purchases, and more. While this helps personalize the customer experience, there are questions about the apparent lack of genuine consent for these companies to access our personal information.

3. AI and the environment

Some AI models are large and require a lot of energy to train on data. While research is underway to devise energy-efficient AI methods, more could be done to incorporate environmental ethical concerns into AI-related policies.

Additionally, the World Economic Forum announced seven evolving guidelines to ensure AI remains human-centered. These include empowering humans, minimizing bias and discrimination, centering use and deployment on privacy, applying human oversight to maximize safety, establishing accountability, deploying AI transparently, and keeping sustainability in mind.

How to create more ethical AI

Creating more ethical AI requires a closer look at the ethical implications of policy, education, and technology. Regulatory frameworks ensure that technology benefits society, rather than harming it. Governments around the world are beginning to enforce ethical AI policies, including how companies will deal with legal issues in the event of bias or other harm.

Anyone encountering AI should understand the risks and potential negative effects of unethical or fake AI. Creating and distributing accessible resources can help reduce this type of risk.

Although it may seem counterintuitive to use technology to detect unethical behavior in other forms of technology, AI tools can be used to determine whether video, audio, or text is fake. These tools can detect unethical data sources and bias Better and more efficient than humans.

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