7 Key Questions You Need To Answer Before Implementing Ethical AI
According to ethical AI statistics, 90% of organizations who have adopted ethical artificial intelligence said they know about at least one instance where artificial intelligence has created ethical issues for the business. The number of executives who were aware of discriminatory AI bias issues has also jumped from 35% to 65% in a short span of few years. 69% said that they are aware of the issues associated with transparency of ethical AI.
All these statistics point towards the growing concerns around ethical artificial intelligence. With more and more businesses jumping on the AI bandwagon, you might be inclined to do the same. Before you do, it is important to have a basic understanding of ethical AI, best practices and risk associated with it otherwise, it could do more harm than good to your organization.
To implement artificial intelligence which is ethical, responsible and safe for all parties, it is important to have a basic understanding of ethical AI. In this article, you will learn about seven important questions that you must answer before implementing ethical artificial intelligence in your company.
7 Questions You Must Answer Before Adopting Ethical AI?
Here are seven questions you need to answer before adopting ethical artificial intelligence in your organization.
1. What is Ethical AI?
Ethical AI is basically a set of techniques and moral principles to govern the development and responsible use of artificial intelligence technology. It also looks at how artificial intelligence is impacting all stakeholders whether they are your employees, customers or suppliers. The core objective is to prevent misuse of AI and eliminate bias from AI based systems. To ensure this, businesses will have to designate AI teams who are tasked to eliminate bias and ensure equal representation and data privacy of all stakeholders.
2. Is AI Ethical By Default?
Whether it is technology in general or artificial intelligence in particular, most organizations will look at it as unbiased and neutral. Unfortunately, that is not true. After all, it is also created by humans. You should stop comparing any technology, especially artificial intelligence as neutral and unbiased. Instead, you should look for ways to govern it, minimize the possibility of its misuse and find ways to reduce bias.
This automatically means that some kind of bias will automatically make their way into AI based algorithms. An AI model is as good as the data you feed to train it or the human behind its development. It will be almost impossible to eliminate bias altogether but we can certainly reduce its impact, through the use of ethical data collection. Improve the quality of data and sources of data and keep a close eye on the decisions AI based systems are making. You can also put them under a human who will vet their decisions before approving them.
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3. Is Ethical AI a Big Enough Problem?
Did you know that 60% of organizations have come under legal scrutiny due to AI based decisions? 22% of organizations have to deal with customer backlash due to AI based activities and decisions. That is not all, 45% of users who had a negative experience with AI not only share it with others but also stop engaging with your organization in the future.
These numbers might paint a gloomy picture but most businesses are preparing themselves to deal with that challenge. We are seeing a massive number of AI based businesses create an AI charter to lay down the guidelines for safer AI development and implementation.
4. How Does Diversity Impact Ethical AI?
You need a culturally diverse team to identify and mitigate biases in AI based systems. You must have a human in the loop approach when managing artificial intelligence. This means that algorithms programmed by humans will have to go through the stringent review process. If some biases were found, they need to be corrected before put in development and deployment phases. Diversity of data sources and data types can increase bias and force AI systems to make skewed decisions.
5. How Other Businesses are Coping With Ethical AI Risks?
As mentioned before, your AI systems will be as good as the data you feed them. The first thing you need to do to eliminate bias is to clean up your data. Use accurate data to train your AI models and they will give correct output. Always test AI based models for biases before they can be implemented.
Some businesses are using open source toolkits to detect bias in datasets while others are using open source machine learning libraries to minimize data bias. You can also use tools available for identifying problems with algorithms as well as bias mitigating algorithms for this purpose.
6. Is Ethical AI The Sole Responsibility of Your IT Department?
Another common misconception businesses have about ethical AI is that it is the sole responsibility of the IT department. Other departments don’t need to play their part. You should make it a shared responsibility instead of putting all the burden on the IT department. You need to create processes, establish guidelines and lay out a comprehensive framework for the use of ethical AI. Your IT department can not do it all alone. They need contribution from all other functional units and stakeholders to make this a success.
7. Will Artificial Intelligence Take My Job?
Most people think of artificial intelligence as their enemy as they think that it will take their jobs. Well, this might even be true to a certain degree but what they don’t tell you is that it will also create millions of jobs. What’s more, AI will not immediately replace humans but will augment them. There is no denying that AI will take over jobs but those jobs would be repetitive mundane tasks. As AI matures, we might see it go after more complex jobs as well. There are certain things that humans can do better than AI but we might see AI catch up in that department as well.
Which is the most important ethical AI question in your opinion? Share it with us in the comments section below.
Author’s bio
Irfan Ak is an tech savvy & content strategist at Branex. It’s a web and app development company in Canada. He is a regular contributor on various websites. He has worked with several brands and created value for them.
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