Ethics and Bias in AI

Ethical considerations and the potential for bias are critical as Artificial Intelligence systems become prevalent in society. Responsible AI development seeks fairness, transparency, and accountability while maximizing societal benefits and minimizing harms. It is essential to navigate the complex challenges of fairness, data privacy, and security to foster trust and social responsibility in AI systems.

Sections

  • 12

    Ethics And Bias In Ai

    Ethics and bias are critical aspects of AI development, focusing on fairness, accountability, and data privacy.

    Learning Practice

  • 12.1

    Introduction

    Ethical considerations and biases in AI are crucial as these systems become commonplace, emphasizing fairness, transparency, and respect for rights.

    Learning Practice

  • 12.2

    Fairness And Accountability

    This section discusses the importance of fairness and accountability in AI, focusing on preventing discrimination and establishing responsibility.

    Learning Practice

  • 12.2.1

    Fairness In Ai

    Fairness in AI entails making decisions without bias against individuals or groups based on sensitive attributes.

    Learning Practice

  • 12.2.2

    Accountability

    Accountability in AI necessitates clear responsibility for decisions made by AI systems.

    Learning Practice

  • 12.3

    Ai And Social Impact

    AI has the potential to positively influence society but also poses risks such as reinforcing inequalities and job disruption.

    Learning Practice

  • 12.4

    Data Privacy And Security

    This section discusses the vital aspects of data privacy and security in AI, emphasizing the need to protect sensitive information.

    Learning Practice

References

Chapter 12_ Ethics and Bias in AI.pdf

Class Notes

Memorization

What we have learnt

  • Ethical considerations are ...
  • Fairness in AI requires mit...
  • Data privacy and security a...

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