Artificial Intelligence has been changing the world around us for some time now. From self-driving cars to healthcare, AI is more integrated into daily tasks. AI can transform the world around us for the better. It is essential to note that with the emergence of self-driving cars, AI can make increasingly complex decisions, and we risk letting technology handle entire industries and societies.
In this blog, we will examine the ethical, practical, and social issues surrounding AI and explain why fully trusting machine-driven processes is difficult.
The Dark Side of AI: Can We Trust Machines Decisions?
Many people find it scary to entrust AI with important decisions. While AI can enhance services with precision and creativity, relying on such advanced technology raises a trust issue. Regardless of the arguments to the contrary, the adverse consequences of AI decisions become visible when technology is not well understood, controlled, or deployed correctly.
The below examples demonstrate that AI is not immune to the same prejudices and inequalities that exist in human decision-making.
1. Algorithmic Bias and Discrimination
Culture and context mostly determine what an AI system considers acceptable. One of the most important areas of concern is the ethical dilemmas that arise from algorithmic biases in society and AI decision-making. For example:
- Criminal Justice: With the help of AI, prediction of re-offending is one of the primary tasks for the US criminal justice AI algorithms. The majority of such algorithms are biased towards race.
- Hiring Algorithms: AI is designed to parse through CVs through a set of pre-defined methodologies. It will tend to get more CVs from a defined group of people instead of a wider group of people due to the biases.
2. Lack of Transparency and Accountability
AI is referred to as a “black box”. This suggests that AI can perform actions relying on data. In crucial sectors such as medicine, finance, and law enforcement, the absence of justification for how decisions were made is extremely concerning. For example:
- Health Care: When AI attempts to recommend the most suitable medical attention to a patient. Then, both the patient and the physician may anticipate deficiencies regarding why a certain recommendation was made.
- Finance: When attempting to secure a loan, advanced machine learning models approve applications based on criteria that the candidates do not know or understand. Rejecting them without explanation causes anger when people feel wronged.
The absence of explanations compiled for AI decisions makes it nearly impossible to ascertain who is guilty if something fails to work properly. This accountability can cause distrust in systems built on artificial intelligence technology.
3. The Risk of Over-Reliance on AI
Advances in artificial intelligence incorporation into healthcare are not without mistakes. AI systems making it increasingly autonomous come with their consequences. Moments where machines solely decide on a matter with such low human intervention are a risk yet to be fully understood. Possible harms include AI failing at intuition, empathy, and ethical reasoning. For example:
- Autonomous vehicles: As with self-driving cars, AI’s role as the primary decision maker poses a serious risk of an adverse overall scenario that the self-governed machines will have to handle without harm.
- Healthcare: An AI system may recommend a particular plan depending on data from thousands of similar cases. Making crucial decisions based on AI creates the distinct possibility of having these decisions not consider the patient’s best interest.
4. Data Privacy and Security Concerns
Privacy and security apprehensions have always been a factor when artificial intelligence systems require significant amounts of information for analysis and making decisions.
- Facial Recognition: AI-powered facial recognition technology is used for surveillance, security, and even retail. If this technology is misappropriated, individuals could be surveilled without permission, resulting in danger.
- Social Media Algorithms: Systems on platforms such as Facebook and Instagram that gather data on individual activity and preferences serve subject sites using AI. While this could be helpful for the intended user, it puts them at risk of exploitation of personal data because AI could be used to capture and sell personal data infinitely without any permission.
Implementing AI without sufficient privacy measures can breach security and threaten personal privacy.
5. Ethical Concerns in Autonomous Weapons
Autonomous weapon systems are another automatic decision-making industry AI dark feature. These autonomous weapons can decide whether or not a person lives or dies without any human effort. They can target and kill an individual using a filter. Such forms of weaponry extensive ethical questions such as:
- If an autonomous weapon makes a mistake or causes harm, who is held responsible for the damage?
- If a machine learning algorithm is able to deeply analyze a combat zone through advanced sensors, will it be able to autonomously determine which targets to eliminate?
The morality of using AI in warfare is alarming and draws attention to the potential consequences of relying on machines in complex decision-making processes.
Can We Trust AI Decisions?
Different factors affect the required outcomes of AI decisions, including:
- Transparency: If AI systems are required to justify their decisions, they must explain the steps they take and actively present how they made them.
- Accountability: Those who create AI systems and those who use them must be held accountable for any of their actions in the use of an AI system, and there should be consequences for any actions that misuse those systems.
- Bias Mitigation: Training data and algorithm biases will not disappear without effort. Developers are responsible for continuously improving AI bias training data algorithms to achieve the desired effects.
- Human Oversight: While AI can handle repetitive tasks, human judgment should remain in place, especially for decisions involving ethics and empathy.
Conclusion
The community must make certain that as AI continues to develop along its current trajectory, the systems are put in place with ethical precautions and care in such a way that does not cause damage. Machines can make better decisions than humans, but humans often struggle to know when the machine’s decision-making is actually more accurate, based on research by ESMT Berlin.
For the time being, knowing fully well the restrictions and hazards AI brings along, as well as being alert and frustrated by it, humanity has to approach AI decision-making with great discernment.
