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Answer :
Fairness in AI involves ensuring equitable treatment, transparency, and accountability in AI decisions, similar to helping children of different heights see a baseball game by providing appropriate support.
In general, in artificial intelligence (gen AI), the fairness principle entails making sure AI systems are impartial and that their choices and acts are just. The goal of AI fairness is to develop algorithms that treat every person equitably and do not give preference to any particular group. This is accomplished by several crucial factors:
Important Elements of AI Fairness:
- Just Treatment: Guaranteeing that each person or group is treated fairly according to pertinent standards. For instance, a hiring algorithm ought to assess applicants exclusively on the basis of their credentials and expertise, without taking into account any extraneous variables like gender or color.
- Transparency: The decision-making process of AI systems ought to be apparent to users. This guarantees that the procedure adheres to fair principles by enabling stakeholders to comprehend and trust it.
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The principle of fairness in generative artificial intelligence (Gen AI) involves ensuring that AI systems treat all users and applicants justly and equitably.
Fairness in Gen AI means that outcomes generated by these systems should be unbiased and just for all individuals. This includes making sure that no group is unfairly advantaged or disadvantaged.
- Procedural Fairness refers to the fairness of the process used to reach outcomes. In the context of Gen AI, this would mean that the algorithms and data used to generate results operate transparently and do not favor certain individuals or groups over others.
- The consequentialist approach is often approached from a consequentialist perspective, meaning that the focus is on the outcomes of AI decisions. Systems must be designed to prioritize fairness for the greater good while minimizing harm to any particular group.
- Achieving fairness is complicated since different individuals or groups have different needs and backgrounds. A policy designed to be fair for one group might inadvertently disadvantage another. Therefore, it’s essential to strike a balance.
- Effective fairness in Gen AI necessitates the acknowledgement of diverse backgrounds and experiences, which can be facilitated by inclusive policies, such as affirmative action that level the playing field for underrepresented groups.
