In What Situations Should AI Be Avoided?

Artificial Intelligence (AI) has revolutionised various industries, offering unprecedented efficiencies and capabilities.

However, it’s crucial to recognise that AI isn’t a one-size-fits-all solution. There are specific areas where AI should be used with caution or avoided altogether due to potential risks and ethical concerns.

While we won’t talk about specific industries, we will describe general scenarios and use cases where we should not use AI or be cautious when doing so.

Examples of where you shouldn’t use AI (or use it with caution!) and why

High-stakes decision-making: AI should not be used in scenarios where decisions have significant consequences on human lives, such as in medical diagnoses, hiring for jobs or legal judgments.

These are situations that require human intelligence and AI lacks the ability to understand and respond to human emotions effectively. In situations that require empathy and emotional intelligence human interaction is crucial as ethics must be considered to navigate the moral complexities of these decisions. We must also understand the lack of transparencey we have when using complex deep learning systems which can be quasi black box; it can be difficult to work out why decisions are made which is essential to know in high stakes scenarios as there has to be accountability.

Due to these reasons, the risk of errors, biases, and lack of accountability can lead to severe legal repercussions.

Sensitive data handling: AI systems should be avoided in situations involving highly sensitive personal data, such as financial information or health records. The potential for data breaches and misuse is too high. Whether you know it or not, all public AI models are consistently training and learning based on the information you input, to use publicly. and the consequences can be devastating.

When permission isn’t given: Using AI to collect or analyse data without explicit consent can lead to privacy violations. It’s essential to respect user privacy and obtain permission before using AI in such contexts.Without explicit permission, individuals then lose control over their highly personal information, which can erase trust and lead to many regulatory issues, such as fines under laws like GDPR or CCPA. Legal risks aren’t all you have to worry abut either – failing to obtain consent can majorly damage an organisation’s reputation, potentially causing loss of customers and business partnerships.

Emotionally driven situations: AI lacks the ability to understand and respond to human emotions effectively. In situations that require empathy, such as counselling or customer service for sensitive issues, human interaction is crucial to provide the necessary emotional support. Imagine discovering that your “therapist” is actually an AI, storing all your private information and potentially sharing it publicly if another user requests it.

Ethical considerations when using AI

Bias and fairness: AI systems can perpetuate and even amplify existing biases present in the training data. To minimise bias and promote fairness, it’s essential to ensure that AI models are trained on diverse and representative datasets or we risk biased decisions that can lead to unfair and discriminatory outcomes, which can have serious consequences for individuals and society.. To this end, there is a very popular coding package called Fairlearn which empowers Data Scientists to improve the fairness of their AI systems using their Python Toolkit.

Transparency and accountability: Artificial Intelligence systems should be 100% transparent in their operations, and there should be clear accountability for their decisions. Users should understand how AI systems work and have the ability to challenge and rectify decisions made by AI. If we know why a decision was made then so we can ensure they’re fair and reliable, so that?AI remains a tool for positive, fair outcomes rather than a source of unchecked authority

Privacy and security: Protecting user privacy and ensuring data security are paramount. AI systems should adhere to strict data protection regulations and implement robust security measures to prevent unauthorised access and data breaches.

Human oversight: AI should augment human capabilities, not replace them. Human oversight is crucial to ensure that AI systems operate within ethical boundaries and make decisions that align with human values and societal norms.

Informed consent: Users should be informed about the use of AI and its implications. Obtaining informed consent ensures that users are aware of how their data is being used and the potential risks involved.

Environmental impact: The development and deployment of AI systems can have significant environmental impacts due to the energy consumption of data centers and computational resources. It’s important to consider the environmental footprint and strive for sustainable AI practices.

To summarise

AI holds immense potential to transform our world for the better, but it must be used responsibly. By understanding where AI should not be used and considering the ethical implications, we can harness the power of AI while safeguarding human values and societal well-being.