Artificial Intelligence is undoubtedly the most advanced technology in today’s modern times. It has the ability to replicate human thinking and activities without the least programming and training. But what matters is the quality and quantity of initial training data. In the further sections, we will let you know why.
From healthcare to manufacturing, and services to finance, artificial intelligence has found its application in every nook and corner. A McKinsey report has predicted that by 2030, AI could contribute around $15.7 trillion to the global economy. But there is a great challenge to address: AI Ethics.
What is AI Ethics?
AI ethics refers to the field that is responsible for the ethical implications of developing and using artificial intelligence.
It is a set of principles that guides various stakeholders using AI such as AI Professionals, government, organizations, or anyone who is developing or using AI models or AI systems to use this technology ethically and responsibly. This might include taking a safer path that doesn’t harm humans, the environment, or organizations. AI ethics may include several processes including avoiding bias and ensuring user data privacy.
There are two major ways in which AI ethics can be implemented:
- Code of ethics in organizations
- Regulatory frameworks designed and implemented by Government
The discussion on AI ethics, its implementation, and bias in algorithms has always been prevalent, and it is a positive sign that AI leaders are taking positive steps to strengthen AI ethics for a responsible society.
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Why is AI Ethics Important?
Unregulated AI development can lead to serious consequences in the world. There are chances that there could be biases in training data which could prove to be fatal for some particular sections of society or particular demography. Such biased data can lead to discriminatory outcomes as was found in the 2022 Algorithmic Justice League Report where racial bias was present in loan approval algorithms.
Not only that, training AI models require collecting vast amounts of personal data as well, giving rise to serious data privacy risks. Last year, a survey by the Pew Research Center found that 72% of Americans have positive views regarding to widespread adoption of AI and believe it has more positive outcomes than negative consequences. But 38% also worry that AI could be used to manipulate people or make biased decisions.
Therefore, it becomes important to check for ethical considerations while developing and applying AI technology.
Ethical challenges of AI
AI ethics and standard consists of several key points that must be followed in ethical AI development:
- Fairness and Non-Discrimination
It should be noted that AI algorithms do not unnecessarily exaggerate societal biases. While training AI models and systems, diverse datasets should be taken along with proper human oversight to prevent such biases.
- Transparency and explainability
It is very important for AI professionals and stakeholders to understand how AI arrives at a particular decision. Therefore, transparency and explainability are important that will help to identify and address if there are any kind of biases which will further strengthen user trust.
- Data Privacy
The sensitive and confidential user data must be protected during the design, development, and deployment of AI. Proper security measures should be implemented to ensure these data are safe.
- Accountability
If heavily relying on AI, then a clear line of responsibility needs to be established. AI systems can make decisions that could impact people’s lives, and therefore proper accountability should be there.
- Safety and Security
A thorough testing is mandatory before deploying any AI model or system for public use. This will ensure the security and safety of the general public and society.
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How to Mitigate These AI Ethical Challenges?
AI leaders must consider the following points while designing an ethically sound AI system:
- The development team should be diverse and inclusive. This means the teams have professionals from diverse backgrounds who can be highly effective in identifying and addressing potential biases that could occur in AI models
- Continuous monitoring and control loops should be mandatory. Human oversight is the most essential thing, especially in high-stakes situations to ensure the responsible use of AI
- Designing a robust regulatory framework is essential. It will act as a guide to ethical AI development and deployment, that will help maintain a balance between innovation and ethical considerations.
Conclusion
AI has huge potential to improve how we live and work. But it is also important that AI is developed deployed and used ethically. While government and AI leaders will do their job of designing effective regulatory frameworks, it is the AI professionals and regular users who must check AI technology is not misused, and any bias in the algorithm should be reported on time to avoid further exaggerating any existing societal issue. Maintaining and strengthening AI ethics should be the job of a particular segment of professionals or departments, but it is the duty of all.
