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Generative AI Data Ethics: Expert Offers 3 Main Considerations

Generative AI Data Ethics

Generative AI Data Ethics

Solutions Review’s Expert Insights Series is a collection of contributed articles written by industry experts in enterprise software categories. In this feature, Mindbreeze‘s Trey Norman offers commentary on generative AI data ethics and three major keys for organizations to consider.

The example of ChatGPT has undoubtedly taken the artificial intelligence (AI) world by storm. Everyone seems to be talking about it. That said, it is critical to note that ChatGPT is more than just an extraordinary and innovative new language model; it is attached to data ethics concerns.

What is Generative AI?

The chat and generative use cases outlined by ChatGPT has significantly shown people and corporations what is possible when it comes to Generative AI. If you are unfamiliar with Generative AI, this type of AI can generate brand-new content from all sorts of data – data from images, text, audio files, videos, and more. The whole idea is to create new from old.

The potential of generative language models is boundless within enterprises. With that said, there are still hurdles to overcome in order to make the use of these models ethical, responsible, and protective of confidential corporate information.

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Generative AI Data Ethics

ChatGPT and Generative AI Used Ethically

For language models to be successful in a corporate setting, it is necessary for them to be trained on specific company data and for the models to be the sole property of the company. Customer service is a prime candidate for the use of generative AI. Allowing customer service representatives to utilize tools to answer support questions saves tons of time and boosts productivity within a company. The only way to produce proper solutions for customers is for companies to equip their employees with specific and relevant content. For example, access to this data will allow representatives to respond quickly to clients with customized and accurate resolutions. The catch is company data is filled with product details, private customer information, and intelligence not meant for people outside the organization.

Main Ethical Concerns for Corporations and How to Handle Them

The question of “who owns the model?” is essential in the conversations surrounding large language models and especially their refinement training. To protect customer data and maintain high-level trust, a line needs to be drawn over what is considered confidential data and what data belongs to the masses.

Where ChatGPT faces ethical concerns is the presentation of inaccurate or misleading results; portraying text as true while it may be completely false.

Scaping the large amounts of data from the internet means that many of the sources used to conceive content may be questionable resulting in a potentially harmful output. To add, applying the “user input” for further automatic learning improvement may lead to the usage of confidential information if workers submitted private business data as a “query input”. For business use, this makes ChatGPT very scary.

Tying all the concerns together, transparency is the key theme. It is important for companies to consider some questions before going down the ChatGPT path. How did the model make certain decisions? Was private content used for the public?

In addition, conversations surrounding the dangers of using ChatGPT for work-related tasks needs to be discussed amongst leadership and the workforce

AI models cannot simply delete data. Before applying it for business operations, training and education are necessary for corporate use. Companies must avoid employees sharing sensitive data because one misstep results in losing the trust of multiple, if not all, customers and major lawsuits on their hands.

Handing over company secrets is happening in bizarre ways but not intentionally. After using the chatbot in fun ways to answer goofy questions or test the platform for accuracy on an intriguing subject, users begin to think of ways the model can help their everyday lives, including their job – writing a memo or drafting a contract. Once input, the model has that information without any awareness of the individual, and unknowingly it could be used to generate content for millions of other users. Just like that, company secrets and private information are out in the world. The lack of understanding of the models’ process is why teaching the workforce about the potential risks is so significant during the ongoing craze of ChatGPT and other existing language models. A blog published by Bruce Schneier outlines a Business Insider article reporting Amazon staffers used ChatGPT as a “coding assistant.

A blog published by Bruce Schneier outlines a Business Insider article reporting Amazon staffers used ChatGPT as a “coding assistant.”

ChatGPT is meant for search and answer, but many use cases, like the customer service example, are not a place for ChatGPT at this time – reducing the benefits of the model within the enterprise and creating ethical concerns.

The Overall Message Related to Data Ethics in Today’s AI Environment

Because ChatGPT and other language models alike have forged a path by showing the world what is possible with AI today, other companies will surely follow suit. I am certain many have heard about Google Bard on the horizon.

Not every day the world sees revolutionary applications causing the buzz and news we have seen with ChatGPT. However, like most things, caution has to be taken with all the hype, especially when it involves confidential information that can be swallowed up and spit out to the world.

Due to this craze and significant usage across global industries, protecting the misuse of sensitive data is a top concern for corporations. Taking action by explaining to employees the potential harms and ensuring proper access rights within your company are steps necessary today for establishing ethical data practices and protecting your customers.

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