AI Ethics: What It Is and Why It Matters

“This alliance of the public and private sectors is critical to building AI for the common good,” UNESCO chief Audrey Azoulay said in a statement. All this makes the power and cost involved in the development and smooth running of Machine Learning and Deep Learning a cause for concern. They can also be invisible to humans as to how Machine Learning works is still not fully clear. Leading industry names like Bill Gates have already started voicing their concern about assessing risk before it’s too late. In 2014, it (yes, Eugene Goostman is a chatbot) won the Turing Challenge – turning out to be the first robot to fool almost half of the human raters into thinking that it was human. “AI will save time, allow for increased control over your living space, do boring tasks, help with planning, auto-park your car, fill out grocery lists, remind you to take medicines, support medical diagnosis, etc.

Designed as a semi-systematic evaluation, this paper analyzes and compares 22 guidelines, highlighting overlaps but also omissions.
Being transparent about data collection with your audience, taking conscious steps to understand how AI works, and ensuring confirmation bias is limited.
Later drafts were made publicly available on the
Internet and publicised via Twitter and e-mail to all (then) cited
authors that I could locate.
While AI can help to increase the efficiency and decrease the cost, for example, of interviewing and selecting job candidates, these tools need to be designed with workers lest they end up perpetuating bias.

Systems of power not only determine one’s sphere of action or possibilities, as the systemic view of power highlights, they also constitute a person’s behavior, intentions, beliefs, and more. Foucault is probably most famous for developing this view of power in his work on discipline and biopolitics. The episodic view of power entails that power occurs when one party exercises power over another, for example, by means of force, coercion, manipulation, or through authority. Dahl famously formulated the intuitive notion of power as “A having power over B to the extent that A can get B to do something that B would not otherwise do” (1957, 202). But even though dispositional power appears to be more fundamental than episodic power, the episodic view of power is relevant because it highlights a specific aspect of power, namely the direct exercise thereof. “Decisions impacting millions of people should be fair, transparent and contestable.

The Ethics of AI Ethics: An Evaluation of Guidelines

In this article, I’ll look at the current evolution of AI guidelines and then explain how the technology sector can play a bigger role in their development and implementation. “Clarifai’s mission is to accelerate the progress of humanity with continually improving is ai ethical A.I.,” read a blog post from Matt Zeiler, the company’s founder and chief executive, and a prominent A.I. Later, in a news media interview, Mr. Zeiler announced a new management position that would ensure all company projects were ethically sound.

While the humanitarian precepts of these teachings are valid today, modern technologies and artificial intelligence raise a host of AI quandaries these frameworks simply don’t address. That is a small set of examples, but there are many more that extend to air and water pollution, climate degradation, warfare, finance and investment trading and civil rights. I have explained that a critical theory is aimed at diagnosing and changing society for emancipatory purposes. I then showed that both the big debates in AI ethics and the most common AI ethics principles are fundamentally concerned with either individual empowerment (dispositional power) or the protection of those subjected to power relations (relational power). Approaching AI ethics as a critical theory, by diagnosing AI’s impact by means of a power analysis and the insights of critical theory, can help to overcome the shortcomings of the currently dominant principled approach to AI ethics.

8 Other Topics in AI Ethics

The group produced a deliverable on the required criteria for AI trustworthiness (Daly, 2019). Even articles 21 and 22 of the recent European Union General Data Protection Regulation include passages functional to AI governance, although further action has been recently demanded from the European Parliament (De Sutter, 2019). In this context, China has also been allocating efforts on privacy and data protection (Roberts, 2019). The decisive factor for the selection of ethics guidelines was not the depth of detail of the individual document, but the discernible intention of a comprehensive mapping and categorization of normative claims with regard to the field of AI ethics. In Table 1, I only inserted green markers if the corresponding issues were explicitly discussed in one or more paragraphs.

Announced in March 2023, the center was created to explore the transformative impact of AI on culture, education, media and society. This sample also suggests that self-efficacy (conﬁdence in using technology) and anxiety (worry about using technology) were found to be important in both rule-based and outcome-based views regarding AI use. “Teachers who had more self-advocacy with using [AI] felt more confident using technologies or had less anxiety,” said Aguilar. “Both of those were important in terms of the sorts of judgments that they’re making.” Google described the change in an annual report on AI principles work as ensuring “more centralized governance across all Google product areas,” but some team members feared it would tilt RESIN’s work more toward protecting Google than preventing harm to consumers.

One branch, machine learning, notable for its ability to sort and analyze massive amounts of data and to learn over time, has transformed countless fields, including education. It sets the first global normative framework while giving States the responsibility to apply it at their level. UNESCO will support its 193 Member states in its implementation and ask them to report regularly on their progress and practices”, said UNESCO chief Audrey Azoulay. Contrasting dimensions in terms of the theoretical framing of the issue also emerged from the review of Jobin et al. (2019), as regards interpretation of ethical principles, reasons for their importance, ownership and responsibility of their implementation. This also applies to different ethical principles, resulting in the trade-offs previously discussed, difficulties in setting prioritisation strategies, operationalisation and actual compliance with the guidelines.

Engineers and developers are neither systematically educated about ethical issues, nor are they empowered, for example by organizational structures, to raise ethical concerns. In business contexts, speed is everything in many cases and skipping ethical considerations is equivalent to the path of least resistance. Thus, the practice of development, implementation and use of AI applications has very often little to do with the values and principles postulated by ethics. The German sociologist Ulrich Beck once stated that ethics nowadays “plays the role of a bicycle brake on an intercontinental airplane” (Beck 1988, 194). This metaphor proves to be particularly true in the context of AI, where huge sums of money are invested in the development and commercial utilization of systems based on machine learning (Rosenberg 2017), while ethical considerations are mainly used for public relations purposes (Boddington 2017, 56).

Global Forum on the Ethics of AI 2024

In the study, Aguilar concluded that teachers are “active participants, grappling with the moral challenges posed by AI.” Educators are also asking deeper questions about AI system values and student fairness. While teachers have different points of view on AI, there is a consensus for the need to adopt an ethical framework for AI in education. Google’s Responsible Innovation team, known as RESIN, was located inside the Office of Compliance and Integrity, in the company’s global affairs division. It reviewed internal projects for compatibility with Google’s AI principles that define rules for development and use of the technology, a crucial role as the company races to compete in generative AI. RESIN conducted over 500 reviews last year, including for the Bard chatbot, according to an annual report on AI principles work Google published this month. Greg Sherwin, vice president for engineering and information technology at Singularity University, responded, “Explainable AI will become ever more important.

The conversation around AI ethics is also important to appropriately assess and mitigate possible risks related to AI’s uses, beginning the design phase. The Business Council for Ethics of AI is a collaborative initiative between UNESCO and companies operating in Latin America that are involved in the development or use of artificial intelligence (AI) in various sectors. AI actors should promote social justice, fairness, and non-discrimination while taking an inclusive approach to ensure AI’s benefits are accessible to all.

The difficulty of allocating punishment

is sometimes called the “retribution gap” (Danaher

2016a). The more common ethical problems in driving, such as speeding, risky

overtaking, not keeping a safe distance, etc. are classic problems of

pursuing personal interest vs. the common good. Programming the car

to drive “by the rules” rather than “by the interest

of the passengers” or “to achieve maximum utility”

is thus deflated to a standard problem of programming ethical machines

(see

section 2.9).

Several tech-companies already offer tools for bias mitigation and fairness in machine learning. In this context, Google, Microsoft and Facebook have issued the “AI Fairness 360” tool kit, the “What-If Tool”, “Facets”, “fairlern.py” and “Fairness Flow”, respectively (Whittaker et al. 2018). As activists, researchers, and journalists voice concerns over the rise of artificial intelligence, warning against biased, deceptive and malicious applications, the companies building this technology are responding. Start-ups, many are creating corporate principles meant to ensure their systems are designed and deployed in an ethical way. Ethics is a set of moral principles which help us discern between right and wrong. AI ethics is a multidisciplinary field that studies how to optimize AI’s beneficial impact while reducing risks and adverse outcomes.

Another justification for competitive thinking is provided by the military context. If the own “team”, framed in a nationalist way, does not keep pace, so the consideration, it will simply be overrun by the opposing “team” with superior AI military technology. In fact, potential risks emerge from the AI race narrative, as well as from an actual competitive race to develop AI systems for technological superiority (Cave and ÓhÉigeartaigh 2018).

Most importantly, it ignores the
nature of automation, which is not simply about replacing humans, but
about allowing humans to work more efficiently.
Approaching AI ethics as a critical theory, by diagnosing AI’s impact by means of a power analysis and the insights of critical theory, can help to overcome the shortcomings of the currently dominant principled approach to AI ethics.
Making mandatory to deposit these algorithms in a database owned and operated by this entrusted super-partes body could ease the development of this overall process.
Arguably the main threat is not the use of such weapons in
conventional warfare, but in asymmetric conflicts or by non-state
agents, including criminals.
The deal obliges the signatories to “guarantee human rights in the design, development, purchase, sale, and use of AI”.

Interestingly, caring for something, even a

virtual agent, can be good for the carer themselves (Lee et al. 2019). A system that pretends to care would be deceptive and thus

problematic—unless the deception is countered by sufficiently

large utility gain (Coeckelbergh 2016). Some robots that pretend to

“care” on a basic level are available (Paro seal) and

others are in the making. Perhaps feeling cared for by a machine, to

some extent, is progress for come patients. The use of robots in health care for humans is currently at the level

of concept studies in real environments, but it may become a usable

technology in a few years, and has raised a number of concerns for a

dystopian future of de-humanised care (A. Sharkey and N. Sharkey 2011;

Robert Sparrow 2016). For an overview, see van Wynsberghe (2016);

Nørskov (2017); Fosch-Villaronga and Albo-Canals (2019), for a

survey of users Draper et al. (2014).

Only the first generation of critical theorists explicitly concerned themselves with technology, mostly focusing on its relation to capitalism (Delanty & Harris, 2021). But, the types of technology that these early Frankfurt School members dealt with were nothing like AI and other digital technologies that exist today. Therefore, it is not easy and perhaps not very valuable either, to try to apply their theories of technology to today’s situation. However, that does not have to mean that the tradition of critical theory is not relevant to the philosophy and ethics of technology. Several contemporary thinkers have argued for the relevance of critical theory to understanding the societal role and impact of technology today.