What Is Responsible AI? 6 Key Aspects You Should Consider

Are you starting to use AI in your business or professional practice? What better than to start doing it responsibly?

Game of tennis with artificial intelligence — We'll cover six key aspects to consider around AI and ethics. (Graphic: Envato Elements)

Here we share six key aspects to consider around AI and ethics.

Everyone seems to be talking about AI these days. And with good reason. Being a new tool, it comes with thousands of benefits as well as a series of necessary negotiations and debates to be had.

The aim of this article is to spark conversations around AI and ethics. So, let's get started.

Jump to the six key aspects in this section:

It Must Be Human Centered

Fairness

Avoid Unintended Bias

AI Transparency

Accountability

Protect Privacy and Safety

First Things First: What Is Responsible AI?

Not quite sure what is responsible AI? Responsible AI is focused on designing, developing and using AI with an ethical and beneficial purpose.

AI practices must empower business and individuals, as well as generating a positive impact in society.

According to research led by Accenture in 2022, only 35% of global consumers trust how AI is being implemented by organizations.

While AI is expanding and being customized by individuals, AI ethics must consider fair transparent and accountable practices.

IT Developers Team in Office — Developers must think of responsible AI to design systems with beneficial purposes. Image source: Envato Elements

For example, we've seen recently with the SAG-AFTRA strike some of the ethical issues with AI in the entertainment industry. Part of the petition is to regulate the use of AI generated replicas of actors, which are used without permission or payment to them.

So, what are we missing on AI and ethics? To start exploring the issue, I went ahead and asked Bard (Google's AI experiment). I turned the answer into key questions to start thinking about ethical issues with AI:

How can we make sure ethics of AI are fair for everyone?
How can we make the use of AI transparent and accountable?
What are the consequences of AI for security and user privacy?

Let's go over the six aspects to make a responsible AI use in our work.

6 Key Aspects You Should Consider When Working With AI

After an in-depth research and some help from Bard, we gathered six key aspects of responsible AI from trusted sources from the internet as Accenture, Google AI and Microsoft AI.

We'll go over each of them and explain how you can apply ethics of AI in your work.

1. It Must Be Human Centered

Everything done with AI must keep the user in mind. This means considering societal and environmental impact and well-being. Some of the questions you should ask include:

What positive and negative impacts will AI have in society?
How can we make sure our AI ethics are used for the good?
How is AI changing the way we work and interact with each other?

Diverse Business Team — Responsible AI should consider societal and environmental impact and well-being. Image source: Envato Elements

2. Fairness

Some of the biggest AI ethical issues include systems created with a discrimination bias. For example, in 2018 Amazon's facial recognition software was found to misidentify people of color more often than white people.

To avoid something like this happening, we should make sure our AI systems treat people fairly, regardless of race, sexual orientation, gender, etc.

Some of the questions you should ask include:

Is the AI job recommendation system I'm using rejects job seekers based on their ethnicity or sexual orientation?
Are the AI platforms I'm working with are discriminating against users based on their religion or gender?

3. Avoid Unintended Bias

This one follows up on the principles of fairness regarding ethical issues with AI. Make sure algorithms and the data collected aren't biased against an individual or group of individuals.

Responsible AI must be as representative as possible.

Some practices you could apply for a responsible AI use:

Be mindful of the potential bias the AI systems you're working on might have.
Be mindful of the data you're getting, where it comes from and who is it based on.
For both cases above, try collecting diverse data from different sources and try using algorithms designed to be fair.

Group of diverse people standing in front of a brick wall — Make sure algorithms aren't biased against an individual or group of individuals. Image source: Envato Elements

4. AI Transparency

Many of the AI issues revolve around a lack of transparency. The main question to ask is: how are these systems using our information?

It's important to communicate to users why AI systems make particular decisions. You should also be accountable for any negative impacts your AI systems may present.

Some examples of how transparency could be applied in professional practices:

Let users know how the AI system you're using was trained on or the algorithms it uses.
If your company uses AI to make hiring decisions, you should be transparent about how this system works.
If your company uses AI to recommend products, make sure users understand how this selection is being made.

5. Accountability

According to research led by Accenture, 77% think organizations must be held accountable for their misuse of AI. It's important to hold those responsible for any negative impacts in AI systems.

For example, there was recently a news-worthy case of an AI algorithm used to create Barbie dolls with culturally insensitive and racist representations. There's an evident absence of human oversight and responsible design in the AI process. Even if dolls were created by machine learning, there are actual humans behind its intentions. People must be held accountable for this kind of AI misuse.

6. Protect Privacy and Safety

Last but not least, AI systems should have users' privacy and safety in mind. This means personal and sensitive data must be used ethically.

For example, companies must have clear policies and procedures to protect the data of their users and employees. These policies should also be transparent to all employees who have access to data.

Here are some of the questions we should ask moving forward:

How do we imagine the future of AI?
What are the potential benefits of AI for your business and your industry?
What are the potential benefits of AI for humanity in general?
How can we start covering AI ethical issues now to prevent future crises?

Team Brainstorming Ideas In Meeting — Start brainstorming with your team: *how do we imagine the future of AI?* Image source: Envato Elements

Now that you know what is responsible AI, keep diving in the topic. There's plenty of angles to explore ethical issues with AI as well as its creative potential.

Check out these AI-related articles featured on Tuts+:

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Start The Conversation on AI and Ethics

Let's talk more about ethics and AI. Take the points presented here and share them at your next job meeting or with colleagues in your industry. Start asking questions such as:

What kind of ethical issues with AI have you dealt with?
What are the ethical issues that need to be considered?
What does a responsible AI look like in your work life?

Hope this read will spark a conversation around AI and ethics. It is the task of all of us who work with these tools to extend the dialogue.