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All it takes is a brief Google search to see that there are many concerns surrounding artificial intelligence. From personal biases to transparency in technology development, many are calling for a responsible approach to the use of AI.

It’s no secret that AI is rapidly transforming automotive and many other industries, as well as our everyday lives. Although this can’t be stopped, there has to be ethics involved. With many organizations and individuals freely using AI and ML technology, discussions on critical AI issues are becoming more prevalent.

As a society, we shouldn’t fear artificial intelligence by any means. In the same vein, the technology should be developed and utilized with ethics as part of the foundation. In this article, you’ll get a brief look at crucial ethical considerations in AI development and implementation.

Understanding Ethical Principles in AI

Ethics in AI development must be considered from several different angles. Some of the most common concerns in this space include bias and discrimination, standards in data transparency, and social manipulation and privacy. For a better overview of this topic, the two sections below will highlight a few of the most important ethical considerations when it comes to AI.

1. Privacy and Data Protection

The efficacy of artificial intelligence is heavily reliant on personal data points. As you might expect, this has led to understandable concerns about privacy and security. The same sentiment goes toward surveillance. Many AI technologies collect data in the background of our homes and surroundings through other devices.

While people want to see privacy and data protection measures from development teams, this isn’t the only security measure that matters. Governments and leading industry organizations should create base frameworks that the industry uses as their guide. One might say this could hinder creativity, even in the automotive industry, but data safety has to come first.

2. Potential Bias and Discrimination

These terms might sound odd in the context of AI, but with a little explanation, it will make a lot more sense. You might be surprised to learn that bias and discrimination can exist in an AI model. If trained through historical data, there’s the possibility that AI could develop a bias in how it functions or with the information it provides.

For example, job applications and facial recognition technology are a few spaces where AI has shown bias before. Another leading example would be the law. Examples of this could be handling a simple traffic violation or navigating the consequences of pleading guilty to a DUI in Canada. No matter how specific the case, AI is quickly becoming a part of the process. In short, AI could potentially hinder diversity and affect specific groups of people due to biases and discrimination.

Endnote

The truth is that there’s a lot to consider when it comes to ethics surrounding artificial intelligence. New developments with this AI in automotive and many other prominent industries are only going to become more common. Considering artificial intelligence is evolving at a rapid rate, it’s best to get educated about it as early as possible; not for usability alone, but for the sake of your own privacy and security.