AI And Morality: Bridging The Ethical Divide
Original source: Forbes Technology Council. Published Oct 03, 2024. Written by Prajeet Gadekar, Forbes Councils Member.https://www.forbes.com/councils/forbestechcouncil/2024/10/03/ai-and-morality-bridging-the-ethical-divide/
Vocabulary
cornerstone (noun): an important quality or feature on which a particular thing depends or is based
equitably (adverb): in a fair and impartial manner
implication (noun): to stop developing, growing, or moving
penalise (verb): subject to some form of punishment
propagate (verb): spread and promote (an idea, theory, etc.) widely
unjust (adjective): not based on or behaving according to what is morally right and fair
utmost (adjective): most extreme; greatest
Article
As AI advances, replicating aspects of human cognition, the ethical implications of its decisions and outcomes become increasingly critical. The intersection of AI and morality is a pressing reality that demands our immediate attention.
Lack of ethical considerations can cause serious, sometimes irreversible harm. For example, healthcare algorithms can maintain racial biases, leaving some patient groups underdiagnosed and underserved. Similarly, AI recruitment tools may favour certain demographics while unfairly penalising others. These problems often prompt organisations to take action only after the damage is done. It's crucial to be proactive and intentional in bridging the gap between AI and morality.
1. Building A Fair System
Unchecked biases in training data can very well propagate and exaggerate biases. This can result in unjust, unfair and even discriminatory outcomes, further intensified by the application of AI.
To prevent this, fairness must be ingrained at the foundational level. Start by acknowledging and confronting your own unconscious biases, as these can easily seep into the datasets during data collection and labelling, thereby biasing the AI’s learning process itself. Providing education and training for your workforce is the key.
Vigilantly audit your training data to identify and correct missing, skewed or inaccurate information. Regularly retrain and enhance your models, drawing on diverse datasets to reflect the full spectrum of human experience.
Furthermore, prioritise accessibility and inclusivity in your AI systems. This is not just about fairness, it's about building solutions that serve and are representative of the diverse populations they impact.
2. Honouring Informational Privacy
AI systems feed on vast amounts of data to learn, adapt and evolve. All data utilised must be collected and managed with the utmost care, adhering strictly to data compliance, consent protocols and data protection regulations.
3. Championing Transparency
Transparency is not just a compliance need but a deep-rooted moral obligation. Users deserve to be fully informed and empowered to give genuine consent, understanding exactly how their data is used and the potential risks in outcomes involved. Implement vigorous logging and tracking systems that record and trace the decision-making process of AI systems. These audit trails not only bring accountability but enable transparency.
Upholding these principles ensures that AI functions not just with intelligence but with integrity, fostering trust and accountability at every step.
4. Ensuring Regulation
The U.S. is making strides in this direction to protect the rights of its civilians when it comes to the implications of leveraging AI-based systems. They put forth the blueprint for an AI Bill of Rights, which is "an exercise in envisioning a future where the American public is protected from the potential harms, and can fully enjoy the benefits, of automated systems." It is based on the core principles of:
Safe and effective systems
Algorithmic discrimination protections
Data privacy
Notice and explanation
Human alternatives, consideration and fallback
While the AI Bill of Rights is at the moment non-binding and does not constitute U.S. government policy, it does provide a foundation and framework for how organisations can start thinking about any future legislation that they can be ready for.
The EU is further ahead, having put forth the AI Act. The AI Act is viewed as the world’s first comprehensive AI law to regulate AI and ensure better conditions for the development and use of the technology. The AI Act is bound by rules that establish obligations for providers and users depending on the level of risk from artificial intelligence, subject to assessment.
The key here is to be aware and understand the geographies your system operates in. Beyond just checking the box for compliance or mandates, these regulations are deep-rooted to protect the rights of its civilians and echo themes for fairness, transparency and privacy.
5. Engineering With Integrity
In today’s rapidly advancing technological landscape, upholding a robust code of ethics is imperative. Organisations must ensure that trust, integrity, responsibility, accountability, fairness and respect are the cornerstones of every action taken by their employees.
As AI becomes increasingly integrated into various aspects of our lives, embedding these ethical principles into the design and development of AI systems is critical. This commitment ensures that AI serves humanity responsibly, transparently and equitably.
In Conclusion
The decisions we make now in how we design, build and govern AI systems will shape the deep-rooted presence of morality, fairness and ethics that these systems will consume. This requires a committed, proactive approach and an intentional mindset by embedding ethical principles into every stage of the AI lifecycle—from data collection to model deployment and beyond. This means continuous monitoring of outcomes, revisiting ethical guidelines and adapting to new challenges as they arise.
In the longer run, the success of AI will be measured by the trust it fosters and the fairness it upholds, not merely by the outcomes it generates. By prioritising ethics in AI, we have the opportunity to create systems that not only enhance human potential but also reflect our morals and values as a society.
Discussion
1) What do you think about this topic?
2) Do you believe unchecked biases in training data can very well propagate and exaggerate biases?
3) Do you think the blueprint for an AI Bill of Rights would be effective, or does another solution need to be found?
4) Do you think organisations will ensure that trust, integrity and responsibility are the cornerstones of every action taken by their employees?
5) Is this the first time we have had problems with morals and ethics in relation to technology?
Extra Resources
Vocabulary Practise: Wordwall