Applying AI in an Ethical Way: Is It Possible?

Artificial intelligence is all over the news, but for every person hailing the technology for its ability to revolutionize work, critics are citing the errors and problems that AI creates. The reality of AI is somewhere in between. As a novel technology, AI has flaws and limitations, but overcoming them and reaping the benefits of AI integration requires an ethical approach to the technology’s use.

Why transparency is essential for ethical AI adoption

The foundation of an ethical approach to artificial intelligence is a philosophy of transparency and accountability. First of all, businesses must be transparent about when and how they use AI. Furthermore, there should be transparency in the AI training process — allowing users to see what data is collected and used, and how it’s being used. This not only gives users better control over their experience and security, but also allows them to call attention to their concerns.

While it would be easy to dismiss the criticisms that detractors have levied against AI, innovators who hope to legitimately push the AI industry forward should be willing to accept and address the concerns of users. Often, the individual user can be one of the most powerful tools at your disposal to identify flaws, biases, and inaccuracies in an AI’s output since they monitor only the output they receive, rather than the entire base of users for the software that the developer must monitor.

Avoiding bias in AI use

Another important aspect of ethical AI use is the mitigation of potential bias. When using AI, it’s essential to remember that models maintain the bias with which they are trained. The nature of artificial intelligence is that its output is shaped by the information it receives. AI is dependent on pre-existing data, and if there are any flaws, inaccuracies, or biases in this data, the model’s response will reflect these.

Furthermore, AI models often use user inputs as a foundation for future responses. If inaccurate or biased information is fed into the model by the average user, it could affect that model’s future performance and accuracy.

Thus, much like it’s important for those developing and implementing AI solutions to be receptive to feedback about their use cases, it’s equally crucial for them to remain receptive to feedback about AI’s potential biases. For example, developers should create an interface for users to report any biases or inaccuracies they may discover. Developers should also make an active effort to ensure that the teams creating and developing these AI programs come from diverse backgrounds, as this will help them prevent an additional level of bias.

Data security and ethical AI

Another major consideration when it comes to the ethical use of AI is data security. Since virtually every piece of data input into an artificial intelligence model becomes part of its database, several critics have raised concerns about how AI uses this data.

For example, in industries where users have confidential information — such as the medical or legal fields — improper use of AI could compromise patient or client confidentiality. In more creative fields, feeding copyrightable IP into an artificial intelligence could result in unintended copyright infringement.

AI companies — as well as companies using artificial intelligence — must therefore institute strict user privacy protection standards. For one, AI platforms should educate their users about proper use. Inform users not to input personal data into the software, and ensure that all users have given their informed consent for any type of data usage that may occur, clearly outlining how the platform may use their data for training or future responses. Beyond this, it’s also essential to implement proper data protection measures, including access control and cybersecurity initiatives, to ensure no malicious actors can access user data.

However, the responsibility for the ethical application of artificial intelligence doesn’t stop with the individual, or even the company. Indeed, ethical frameworks must be put into place on a wider scale to establish guidelines and standards to guide the development, deployment, and use of AI to ensure its current and future uses minimize harm, uphold human values, and promote social well-being.

Paving the way for a future of ethical AI

Ultimately, the goal of ethical AI is to create a world where human workers and AI can co-exist and complement one another. Artificial intelligence is a tool that can be used by human workers to significantly increase their efficiency. However, if used irresponsibly, the damage it could cause can be more substantial than the benefits. As such, establishing a clear understanding of best practices will be a key step in the successful integration of AI across industries.

There is no doubt that artificial intelligence is an exciting new technology poised to create a radical paradigm shift in the world as we know it. Still, the successful integration of AI technology requires an ethical approach to its use, emphasizing transparency and data security — ideally through a framework that establishes clear standards and understandings by which businesses hoping to use AI can operate.

Learn more about Intellibus and the ethical way of utilizing Artificial Intelligence.

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About Author

Ed Watal is an AI Thought Leader and Technology Investor. One of his key projects includes BigParser (an Ethical AI Platform and Data Commons for the World). He is also the founder of Intellibus, an INC 5000 “Top 100 Fastest Growing Software Firm” in the USA, and the lead faculty of AI Masterclass — a joint operation between NYU SPS and Intellibus. Forbes Books is collaborating with Ed on a seminal book on our AI Future. Board Members and C-level executives at the World's Largest Financial Institutions rely on him for strategic transformational advice. Ed has been featured on Fox News, QR Calgary Radio and Medical Device News.