AI-Wareness: Ethical Use of AI
CS Seminars and Educational Trips
- Roboethics
- Accountability of an AI
- Transparency and Contestability
- Three laws of robotics, and
- "What, Why, and How" framework
- ethical challenges that AI can pose
The
"What" of AI ethics involves adhering to a set of values, principles,
and techniques that align with widely accepted standards of right and wrong.
These standards serve as a moral compass, guiding the development and use of AI
to ensure that it contributes positively to society. The "Why" is
rooted in the necessity to prevent harm—whether to individuals or society as a
whole—caused by the misuse, abuse, poor design, or unintended negative
consequences of AI systems. As AI becomes more integrated into our daily lives,
the potential for both positive and negative impacts grow, making it essential
to mitigate risks and safeguard against harm. The "How" emphasizes
the role of algorithms in AI systems. By following a sequence of rules or
instructions, these systems can make decisions that ideally reflect ethical
considerations. However, ensuring that these algorithms are designed with
transparency and accountability in mind is key to maintaining trust in AI
technologies.
By applying the
"What, Why, and How" framework—ensuring ethical standards, preventing
harm, and using transparent algorithms—I can contribute to developing AI
systems that are both responsible and beneficial to society.
The discussion of Isaac Asimov's Three Laws of Robotics highlights the crucial need for establishing clear guidelines for AI behavior. These laws emphasize the importance of ensuring that robots do not harm humans and operate in ways that align with human values. In this context, accountability and transparency are essential, as they enable AI decisions to be understood, questioned, and challenged when necessary, reinforcing the ethical use of AI.
The webinar on
ethical AI use highlighted the importance of integrating ethical principles
directly into AI development. On a practical level, this means establishing
clear guidelines that prioritize transparency, accountability, and human safety
in AI projects. For example, when developing algorithms, I can ensure
transparency by documenting the decision-making process, making the system’s
actions understandable and contestable.
Accountability
can be implemented by defining who is responsible for the AI's decisions, which
is crucial for managing risks associated with AI. Adapting the Three Laws of
Robotics into guidelines can further ensure that AI systems prioritize human
welfare, with rigorous testing and ethical reviews before deployment.
Indeed, this
webinar served to extend my knowledge on AI Ethical Considerations. I found the
discussions on accountability, transparency, and ethical challenges imposed by
AI to be particularly edifying. He was able to explain abstruse ideas and put
them in perspective with regards to practical, real-world applications. I
appreciate that it was pointed out how ethics should be integrated into
development from the bottom up. In any case, it was an enlightening session
that kept me engaged all along and provided me with certain helpful means to
put into practice in my projects. I thank the organizers and the speaker for
such an elaborate and engaging experience.
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