Today Artificial Intelligence (AI) has pervaded almost every segment of people’s activity including health, wealth, entertainment and interpersonal contacts. Al as a developing technology entails great benefits and enormous ethical questions that arises daily.

It is the right use of artificial intelligence in such a manner that it will benefit the society, and be independent of at least such biases as might be occasioned by personalities or prejudices of the individuals who develop it. The protection of ethical AI is of paramount importance to avoid augmented/prejudiced information processing, users’ privacy leakage and more importantly, to sustain public confidence in technology.

Ethical AI ensures fairness, transparency, and accountability in decision-making, promoting societal trust in technology.

This concept of ethical Artificial Intelligence can be described as a large umbrella under which several principles and structures that would seek to govern the creation and utilization of the Artificial Intelligence are peaceable. AI ethical concerns relate to the fair usage of AI systems, explaining the reasoning behind decisions, who is responsible for a specific decision, individual’s and data protection and security.

Governments and technical implementers need to formulate how best they can use AI without being a nightmare to humanity. Ethical AI is not only about the absence of moral evils but also about the positive ability to produce, prevent, reduce, distribute, and balance misfortune and good.

The most critical ethical ownership problem facing AI is bias. AI systems learn from data which data is provided, if this data is insensitive to some or the other criteria like race, color, gender, economic status, etc. then what you get is this AI system giving out prejudices. For example, the technologies such as facial recognition have been deemed to be insensitive to the ethnic community, especially in their accuracy of capturing people from that background for racist acts.

Likewise, prejudiced recruiting AI may well allocate jobs to one race more than another increasing employment disparity. To fight bias in Artificial Intelligence, creators have to think about the algorithms’ data selection process, include bias detection mechanisms and monitor AI models’ outputs constantly, removing bias as soon as possible. Ethical frameworks of AI state that choices made by the AI should not be biased and that the AI should include all.

Bias in AI systems stems from flawed data and requires rigorous monitoring and removal to ensure fairness.

Deep learning algorithms, in particular, are known to make up ‘absolutely opaque’ AI models, that means the ways they come to given conclusions are not easily discernible. Such opaqueness has several ethical implications, especially in areas where the use of AI decision making has crucial implications such as in the medical and justice systems. If an AI model refuse credit or job to a person, the reasons must be clear so that the decision making process can be justified to the person affected.

In an effort to increase transparency the AI researchers are working on the techniques known as the explainable AI (XAI) that provides more details to help people understand the decisions made by AI. Transparent AI makes it possible for the user, and even the regulatory bodies, to dissect how an algorithm works, determine whether or not it is accurate in its operations and, if not, how it can be rectified when it produces results that are prejudiced.

As decisions involving AI systems are made, there arises an important question of who is responsible. If an AV gets involved in an accident or an AI-based diagnostic tool produces an undesirable output, it is difficult to decide who is liable; the developer of AV, the user of AV, or the AI system. Since there are explicit matrices of authority and responsibility functions hard time to prosecute the culprits or get a refund.

The public and their representatives must introduce and reinforce strong accountability frameworks that indicate who is liable for decisions that are based on the use of Artificial Intelligence. Recommendations given by ethical AI frameworks include the idea of having watchdogs, periodic check and balances, and well-laid down legal mechanisms and terms of references.

Transparent AI systems and explainable AI (XAI) enhance accountability, crucial in high-stakes fields like healthcare and justice.

Every effective artificial intelligence system depends on the large amount of data input. Nevertheless, the collection and processing of personal information are accepted with great concerns about data privacy. The advancement in the use of AI in surveillance, advertising and facial recognition, individuals’ privacy is in a steadily declining phase.

Most of the AI systems still introduce the user’s personal details into their algorithms, even if the user did not willingly volunteer for that, raising the question as to the use and handling of such information. To address the issue of privacy in AI at organizations, there are significant measures that organizations must put in place regarding data security, these are; encryption, anonymization, and adherence to the GDPR. Ethical AI safeguards the user’s consent, keeps the user’s data safe and discourages users from having their data accessed or used without their knowledge.

AI based automation of employment raises major questions with regards to employment and economy. Of course, AI can increase production rates and improve organizational effectiveness; at the same time, it can contribute to job outsourcing with personnel layoffs in production, transportation, and call centers. The moral question in focus concerns the ability to employ innovation in technology while at the same time ensuring that individuals have work and that their living is not made hard by fast-emerging technologies.

Thus, the governments and organizations must work hard to invest in reskilling and upskilling of employees so that they can easily get a new job. Ethical vision of artificial intelligence should lie in increased efficiency of cooperation between man and the artificial intelligence instead of focusing on replacing human workers.

Safeguarding privacy and addressing employment disruptions are pivotal in maintaining public confidence in AI technologies.

The roles and ethical issues of AI and thus require regulation of their application. AI and related frameworks are currently being investigated in different nations and global organizations for ethical standards. For example, the proposed AI regulation in the EU known as AI Act whose goal is to set the rules for the utilization of AI, which is subdivided into four tiers in terms of risks.

Therefore, regulation cannot be seen as a blockade, but at the same time, it cannot fail to notice that all these work with ethical safeguards. The regulation of such technologies can be carried out in two extremes, either over-regulation or under-regulation. AI ethics is discussed as the establishment of principles that need cooperation involving government, technology companies, academics as well as civil society in establishing policies on the process of application of artificial intelligence.

Disclaimer: The opinions expressed in this article are solely those of the author. They do not represent the views, beliefs, or policies of the Stratheia.

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