“AI Ethics: MIT Press Essential Knowledge Series” – Review and Summary


Mark Coeckelbergh’s “AI Ethics: MIT Press Essential Knowledge Series” is a seminal work that delves into the intricate relationship between artificial intelligence (AI) and ethical considerations. As AI continues to permeate every facet of our lives, the book serves as a timely reminder of the importance of ethical considerations in the design, deployment, and governance of these technologies.

It is a foundational text for understanding the ethical landscape of AI. While it covers a broad spectrum of topics, the ever-evolving nature of AI and its implications means that the discourse on AI ethics is far from over. As professionals, it’s our responsibility to engage with these ethical considerations actively, ensuring that the AI-driven future is equitable, just, and beneficial for all.

Before the review I remind you of some facts:

First, it is important to note that the ethical issues raised by AI are not new. Many of these issues have been discussed for centuries in the context of ethics in (business and government) decision making. They have also been discussed in the context of other technologies, such as nuclear weapons and genetic engineering. However, the rapid development of AI has made these issues more urgent and pressing.

Second, it is important to emphasize that AI ethics is not just a technical issue. It is also a social and political issue. We need to have a public conversation about the ethical implications of AI and to develop policies and regulations that promote the ethical development and use of AI.

Third, it is important to remember that AI is a tool. Like any tool, it can be used for good or for bad. It is up to us to ensure that AI is used in a way that benefits humanity and that does not harm it.


Coeckelbergh’s work is both comprehensive and accessible. He masterfully weaves philosophical concepts with real-world examples, making the content relatable and thought-provoking. His exploration of moral agency in machines is particularly commendable, pushing the reader to question deeply-held beliefs about consciousness, intentionality, and ethics.

The discussion on responsibility and accountability is timely, especially as we grapple with the real-world consequences of AI decisions. Coeckelbergh’s insights into the “responsibility gap” are profound, highlighting the complexities of attributing blame in a world of autonomous systems.

Coeckelbergh’s “AI Ethics” is a must-read for anyone in the AI field. However, as the domain of AI ethics is vast and ever-evolving, it’s crucial to approach this work as a starting point rather than a comprehensive guide. We also need to keep thinking and working on the following themes.

  • Global Implications: AI ethics is not just a Western concern. It would be beneficial to explore the cultural and societal nuances of AI ethics in non-Western contexts. AI ethics should be inclusive. Incorporating perspectives from diverse cultural, socio-economic, and professional backgrounds would enrich the discourse.
  • Economic Impacts: We could benefit from more deeper dives into the economic implications of AI, especially in terms of job displacement and the potential for economic inequalities.
  • Environmental Ethics: As AI models become more complex, their environmental footprint increases. The ethics of AI should also consider the environmental impact of training large models and the sustainability of AI-driven solutions.
  • Transparency and Explainability: As AI systems become integral decision-makers, the ability to understand and interpret their decisions becomes crucial. The ethics surrounding transparency and the right to explanation warrant more attention. Also the methods and techniques being developed in this field need to be scrutinized from an ethics perspective. When do they provide enough information?
  • Human-AI Collaboration: The future is not just about AI but about human-AI collaboration. Ethical considerations around how humans and AI can work together harmoniously are essential.


Coeckelbergh begins by setting the stage, emphasizing the rapid advancements in AI and the subsequent ethical challenges that arise. He introduces the reader to the foundational concepts of AI, ensuring that even those unfamiliar with the technicalities can grasp the ethical implications.

The book is structured around several key themes:

Moral Agency and Machine Ethics

Coeckelbergh delves into the debate over whether machines can possess moral agency. He explores the philosophical underpinnings of what it means to be a moral agent and how this applies to AI systems.

The concept of moral agency traditionally belongs to beings capable of making moral judgments based on a sense of right and wrong. Historically, this has been the domain of humans, and to some extent, certain animals that exhibit rudimentary forms of empathy or fairness. However, the rise of AI challenges this traditional notion.

While the debate on machine ethics and moral agency is far from settled, what’s clear is that as AI systems become more integrated into our lives, these philosophical questions will have tangible real-world implications. It’s crucial to engage with these issues now, laying the groundwork for a future where machines and humans coexist harmoniously.

Machine Learning and Decision Making

At the heart of the debate is the way machines “learn” and “decide.” Unlike humans, machines do not possess consciousness, emotions, or intentions. Their decisions are based on patterns in data and predefined algorithms. Yet, the outcomes of these decisions can have profound moral implications. For instance, an autonomous vehicle might have to decide between swerving to avoid a pedestrian, potentially harming the car’s occupants, or continuing its path, endangering the pedestrian.

Can Machines Possess Morality?

The crux of the issue lies in distinguishing between programmed ethics and genuine moral agency. While we can program a machine to follow ethical guidelines, does adherence to this programming confer moral agency? Most philosophers argue that it does not. Genuine moral agency requires intentionality, understanding, and the capacity for moral reasoning, attributes machines currently lack.

However, as machines become more sophisticated and their decision-making processes more opaque, the line between programmed responses and “decisions” becomes blurred. Some argue that if a machine’s actions are indistinguishable from those of a moral agent, then, in practice, they should be treated as such.

Implications for Responsibility

If we were to ascribe some form of moral agency to machines, it would have significant implications for responsibility and accountability. If a machine makes a “wrong” decision, is it the machine’s fault? Or does the blame lie with the programmers, the users, or the broader system in which the AI operates?

Responsibility, Accountability, and Transparency

The author addresses the “responsibility gap” that emerges with AI systems. Who is to be held accountable when an AI goes awry? The programmer, the user, or the machine itself? It, also, is often difficult to understand how AI systems work and to hold them accountable for their decisions. This can make it difficult to trust AI systems and to ensure that they are used fairly and responsibly. For example, it may be difficult to understand how an AI system that is used to make medical diagnoses makes its decisions. This can make it difficult for doctors to trust the system and to ensure that it is making accurate diagnoses.

Privacy and Surveillance

In an age of data-driven AI, Coeckelbergh discusses the implications for privacy. He touches upon the surveillance capabilities of AI and the potential erosion of individual privacy. AI systems collect and use large amounts of data, which raises concerns about privacy and security. For example, an AI system that is used to recognize faces may collect and store images of people without their consent. This data could be used to track people or to discriminate against them. Another example is an AI system that is used to predict customer behavior. This system may collect and store data about people’s purchase history, browsing habits, and social media activity. This data could be used to target people with advertising or to sell it to third parties.

Bias and Fairness

AI systems can inadvertently perpetuate societal biases. Coeckelbergh delves into the challenges of ensuring fairness in AI outputs and the societal implications of biased algorithms. AI systems are trained on selected data, and if this data or the selection is biased, the AI system will also be biased. This can lead to discrimination and other harms. For example, an AI system that is used to make hiring decisions may be biased against certain groups of people, such as women or minorities.

Autonomy, Empowerment, and control

The author explores the balance between human autonomy and machine assistance. How much decision-making power should we cede to machines, and at what cost? As AI systems become more sophisticated, they may be able to operate autonomously and make decisions without human intervention. This raises questions about who is responsible for the actions of AI systems and how we can ensure that they remain under human control. For example, an autonomous weapon system could kill people without human intervention. This raises the question of who is responsible for the deaths of these people. Another example is an AI system that is used to control a self-driving car. If this system makes a decision that results in an accident, who is responsible?

The future of work

AI is likely to have a significant impact on the future of work, potentially displacing some jobs and creating new ones. This raises questions about how we can ensure that everyone benefits from the economic benefits of AI and that no one is left behind. For example, AI could automate many tasks that are currently performed by humans, such as manufacturing jobs and customer service jobs. This could lead to job losses and unemployment. However, AI could also create new jobs in areas such as AI development, maintenance, and repair. It is important to ensure that people have the skills and training they need to succeed in these new jobs.

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