top of page
  • The Merge

Exploring the Ethical Implications of Artificial Intelligence and Machine Learning

Updated: Feb 25, 2023

Ethical Implications of Artificial Intelligence

Artificial intelligence (AI) and machine learning (ML) are among the most revolutionary technologies of our time. They have the potential to change the way we live and work in ways we never thought possible. You may not be aware of it, but AI is integrated into many of the technologies you use on a daily basis. From Netflix recommending shows you may enjoy, to Google suggesting you book a trip online from your usual airport, AI plays a role in these processes.

However, as we continue to push the boundaries of what is possible with Artificial Intelligence and Machine Learning, it is important that we also consider the ethical implications of these technologies.

What are ethics in AI?

The field of AI ethics aims to establish moral guidelines to direct and inform the creation and application of AI technology. Given that AI is capable of performing tasks that would typically require human intelligence, it is necessary to establish ethical principles to govern it's use just as we have moral standards for human decision-making. In the absence of proper ethical regulations for AI, there is a significant risk of the technology being misused to perpetuate misconduct.

The ethical concerns related to AI can vary greatly depending on the industry, context and potential impact. However, some of the major ethical issues surrounding AI include bias, job displacement, privacy concerns and the potential for AI to be used for deception or manipulation. In the following section, we will take a closer look at each of these issues in more detail.

Bias in Artificial Intelligence

One of the most significant ethical concerns associated with Artificial Intelligence and Machine Learning is bias. AI and ML systems are trained on data, and if the data used to train them is biased, the resulting models will also be biased.

This can lead to unfair and discriminatory outcomes, such as denying job opportunities to certain groups of people or providing biased medical diagnoses. For example, a study by MIT researchers found that a commercially available facial recognition system was more likely to misidentify darker-skinned individuals and women than lighter-skinned individuals and men. This is a clear example of the potential for bias in AI and ML systems. To mitigate this concern, it is important that the data used to train these systems is diverse and representative of the population it will be used on. Additionally, it is important that the developers and users of these systems are aware of potential biases and take steps to mitigate them.

Artificial Intelligence Jobs replacing Humans

Another ethical concern is the potential for AI and ML to take over jobs that are currently done by humans.

As these systems become more advanced and capable, they may be able to perform tasks that were previously only done by humans, leading to job displacement and economic disruption. For example, self-driving cars may eventually replace human drivers, leading to a significant loss of jobs in the transportation industry. While this may bring about efficiency and cost savings, it is important to consider the impact on individuals and communities that rely on these jobs.

Governments, companies and other stakeholders should work together to develop strategies to mitigate the impact of job displacement and support those affected by it.

Transparency and accountability

Transparency and accountability are also major ethical concerns with AI and ML systems. Because these systems can make decisions and take actions without human intervention, it can be difficult to understand how they arrived at a particular decision or action, and to hold them accountable when things go wrong.

This is particularly important in high-stakes applications such as healthcare and criminal justice. It is crucial that these systems are designed in a way that allows for transparency and accountability. This could include, for example, the ability to explain the reasoning behind a decision, or the ability to audit the system's performance.

Privacy concerns

Privacy is probably one of the most pressing ethical concerns of AI and ML, as these systems often require access to large amounts of personal data to function. Privacy is considered a basic human right according to the United Nations Declaration of Human Rights, and several AI applications can pose a significant threat to it.

Advancements in technology such as surveillance cameras, smartphones and the internet have made it easier to gather personal data. There is a risk that this data could be used for nefarious purposes, such as targeted advertising or even surveillance. When organizations are not transparent about the reasons and methods for collecting and storing data, privacy becomes vulnerable.

To mitigate this concern, it is important that individuals have control over their personal data and that the data is handled and stored in a secure and responsible manner.

Impact on society

Finally, there are concerns about the long-term impact of AI and ML on society. As these systems become more advanced and autonomous, they could potentially be used to create autonomous weapons or other tools of war. Additionally, AI and ML systems have the potential to exacerbate existing societal issues such as inequality and discrimination. It is crucial that we consider the long-term impact of these technologies and put in place safeguards to ensure that they are used in ways that benefit society as a whole.

So, how can Artificial Intelligence and Machine Learning be used ethically?

Given the various challenges that AI and ML present, it's natural to question how to mitigate risks when implementing their solutions. Fortunately, there are several best practices for using AI and ML ethically in a business context.

Education and Awareness

First and foremost, it's essential to educate yourself and your colleagues about the capabilities, limitations and potential ethical issues of AI and ML. Instead of ignoring or fearing the potential for unethical use of AI, it's crucial to ensure that everyone understands the risks and knows how to mitigate them.

Develop Ethical Guidelines

Create a set of ethical guidelines that your organization must adhere to. This can be done by consulting with stakeholders, examining industry standards and regulations, and conducting a thorough risk assessment.

Regularly Review and Refine

Since ethics in AI is difficult to quantify, it's important to check in regularly to ensure that your organization's goals are being met and processes are being followed.

Human-First Approach

Control bias by taking a human-first approach to AI and ML. This involves ensuring that your data is unbiased and inclusive. By diversifying the team of individuals working on AI technology, you can ensure that the AI you create reflects the diverse world it was created for.

Transparency and Security

When AI is involved in data collection or storage, it's crucial to educate your users or customers about how their data is stored, what it's used for, and the benefits they derive from sharing that data. This transparency is essential for building trust with your customers, and adhering to an ethical AI framework can be seen as a positive for your business rather than restrictive regulation.

Despite AI being a relatively new field, technology leaders who have been working in the field for many years. Artificial intelligence has become a prevalent force in our daily lives, with many services and devices utilizing AI to make our experiences more convenient and efficient. While it is possible for AI to be used with malicious intent, the majority of companies have implemented ethical principles to minimize any negative impacts.

By adhering to best practices, AI has the potential to enhance nearly every industry, from healthcare to education and beyond. It is the responsibility of those developing AI models to ensure that ethics are considered and the potential impact on society as a whole is evaluated.

When viewed as a means to enhance human intelligence rather than replace it, AI becomes less intimidating. With the proper ethical framework in place, the potential for AI and ML to positively transform the world becomes clear.


bottom of page