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April 19, 2024 - 7 minutes

Ethical AI: Principles for Career Success

Dive into creating ethical and successful artificial intelligence systems.

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Artificial Intelligence

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If you’re already interested in entering the field of artificial intelligence, you’re in a great place: you’ve realized the potential of the incredibly powerful sector and want to prepare yourself to be one of the world’s first AI professionals. But, possibly unbeknownst to you, there’s another significant benefit that comes with being one of the first to take on AI: playing an integral role in the discussion about ethical artificial intelligence. 

As you know, the field of artificial intelligence seeks to teach computers to mimic human decision making, evaluating their options to produce the most human-like response. And while there are innumerable benefits to using artificial intelligence, as the technology has advanced in recent years, the question of ethics has come to the forefront of every AI professional’s mind.

In this article, we’ll first review some of the main ethical debates within the field of artificial intelligence and then give you some tips and tricks for keeping ethics at the center of your AI work. Let’s dive right in.

Ethical Challenges in Artificial Intelligence

Do you remember hearing about robots taking over the world or self-driving cars going rogue and causing havoc? Although these are sensationalized versions of the dangers of AI that probably won’t come to fruition, the ethical dilemmas facing the AI field are very much concerns that need to be taken seriously. 

As computers become more and more autonomous and are able to make increasingly human-like decisions and are subsequently trusted with more frequent and more important decision making, the obvious question arises: how can we ensure that these decisions are being made ethically and securely?

In addition, the AI field faces these challenges: 

  • User privacy: artificial intelligence systems use large amounts of data to learn how to act and this data has to come from somewhere; as companies feed data upon data into their artificial intelligence systems so that they can learn, this data can be susceptible to data breaches or hacks if not properly protected. When dealing with personally identifying information, specifically, AI systems must be built with security to protect user information, in addition to being transparent with users about what’s being done with their data.

  • Bias: although you may think a computer is free of bias, artificial intelligence systems don’t have the complete range of critical thinking skills that are necessary to reflect on all information before making a decision. In addition, AI systems are only as unbiased as the data they learn from; if the data fed to an AI system is full of bias, the outcomes will be extremely skewed. 

  • Confusion about how they work: while AI engineers might have a clear understanding of how AI systems work and what they’re doing with the data they’re fed, your average person may not be willing to trust a computer with major decisions and question the transparency of using an AI system to make decisions. 

  • Misinformation: we’re sure you’ve seen examples of AI systems that produce simply incorrect or untrue results and given how fast misinformation can spread, there is a large ethical concern when it comes to trusting and vetting the information or decisions that come from an AI system.

  • Job security: possibly one of the main concerns when it comes to entrusting AI with more and more responsibilities is if it will take jobs away from humans. As artificial intelligence systems become capable of an increasingly higher number of tasks, ensuring that humans don’t lose their jobs to these tools must be at the forefront of all AI engineer’s minds. 

  • Responsibility: another main concern in the sphere of ethics in artificial intelligence is figuring out who will be responsible when an AI system’s decision turns out to be incorrect or cause damage. Is it the responsibility of the AI system? Or of the engineers that built it? Without a clear answer to who’s responsible for any issues that arise, it’s hard to fully trust the systems. 

Bringing Ethics to the Forefront of Your Artificial Intelligence Work 

There are quite a few things to keep in mind when working with AI systems, right? And here’s a little secret: as the power of AI expands and it takes on even more responsibilities, there will be even more concerns to keep in mind. 

As you dive into your work with artificial intelligence systems, try to keep the following principles in mind so that you’re able to work as ethically as possible with AI. 

Be clear about your ethical principles 

Ethics is subjective–what’s a concern to you may not be to another person and that’s simply a fact. So when you begin your work with an AI system, the first thing to do is meet with your team and establish ethical principles that you want your work to adhere to. This will not only ensure everyone is on the same page, but also guarantee that your entire team is prioritizing ethics when working with the artificial intelligence system. 

When deciding your principles, which will depend on the exact project, of course, make sure you take local and international regulations into account to ensure you’re compliant with any rules relevant to you. 

Prioritize transparency 

While it may be easier to press a button and let AI do its thing, transparency is an essential part of creating an ethical AI system and when prioritizing transparency, there are three key elements: 

  • First, users must know that their data is being used to train AI systems and how it’s being protected. They must, of course, be able to opt in or out of sharing their data with the AI system. 

  • Second, you must be transparent with your use of artificial intelligence systems so that it’s clear to everyone involved that AI is being used, where, and when. 

  • Lastly, how and why artificial intelligence systems are being used must be clear to others so that they know AI systems are part of the entire equation. 

With more transparency comes more trust and the more upfront you are about your use of AI, the better received it will be. 

Focus on security and privacy

We all know that AI systems are trained with data, typically user data, and this is how they learn and become better at what they can do. But this data must be protected to ensure more trust in the system; users won’t want to share personally identifying information if they can’t be sure it won’t be stolen or hacked. 

In addition, all those working with the artificial intelligence system must be trained about privacy and security so that they’re aware of the dangers associated with data leaks and fully comprehend the importance of creating highly functional security systems. 

As you can see, there are quite a few things to keep in mind when creating an artificial intelligence system–the effectiveness and application of AI systems depend on its ethics and how trustworthy it seems to users. Without a strict adherence to ethics, it will be nearly impossible for the AI system to be effective. 

Learning how to properly use artificial intelligence in a wide range of applications is a priority for many and if you’re up for the challenge, consider AI School by Ironhack, our new initiative designed to prepare you for the AI revolution ahead, teaching you what you need to know to reach new heights in your career. 

Up for the challenge? We’ll see you in class!

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