AI Ethics: Navigating the New Frontier in Business

The GAAP Dynamics team (Clark Moeller, Carlo Zuffi, and I, Rian Moses-Hedrick) had a blast making our debut as presenters at the Learning & HR Tech Solutions conference in Orlando, Florida, on April 24, 2024. Our session, AI Ethics: Navigating the New Frontier, was a hit, especially given this year’s heavy emphasis on AI technology. And, if we do say so ourselves, our Star Trek-themed presentation really caught the audience’s attention and got them thinking about the possibilities of AI! This post explores AI ethics, including considerations of challenges such as bias, IP protection, and employee acceptance.

AI is pretty game-changing, right? I mean, it speeds up content creation, sparks new ideas, and boosts productivity like never before. But before we dive headfirst into AI’s awesomeness, shouldn’t we take a step back and ask some tough questions? Like, what about the whole intellectual property thing? Or the risk of cranking out offensive or downright misleading content? And let’s not forget the danger of blindly accepting whatever AI spits out, or the whole deal with employees getting on board with it.

During our presentation, we dove into these ethical dilemmas of AI. Don’t worry if you couldn’t catch us in Orlando; this post will provide you the highlights, along with a link at the time for our presentation slides, and resources!

Overview of Generative AI:

Generative AI, often misunderstood as robots with self-awareness, actually refers to AI tools that generate outputs based on given prompts, pulling from specific pools of data. These tools, like text, video, image, or code generators, undergo extensive training on large datasets to understand patterns within data. However, perceptions of AI vary globally. A study by KPMG International and The University of Queensland revealed a balance between risks and benefits, with cybersecurity topping global concerns. Interestingly, trust in AI applications differs across sectors, with Human Resources being the least trusting.

Now, when it comes to ethical concerns around Generative AI, there’s a laundry list: bias, inaccuracy, misuse, security risks—you name it. Biases in AI stems from the data, not the AI itself, emphasizing the need for transparency. Misuse, including deep fakes and plagiarism, raises concerns about misinformation and legal consequences. Best practices for AI include blending its output with human expertise, being transparent about its use, fact-checking, giving clear instructions, using diverse data, and adhering to guidelines. By mixing human know-how with ethical considerations, businesses can ride the AI wave while keeping trust and integrity intact.

Ethics of AI in data

When it comes to the ethics of AI and data, protecting your company’s intellectual property (IP) is priority numero uno. Steer clear of tossing sensitive company info into open-source AI systems like ChatGPT or AI training platforms to dodge any potential leaks. And don’t forget to slap copyright, watermarking, and trademarking on materials you want to safeguard. Oh, and keep tabs on your data’s usage in AI training sets with tools like haveibeentrained.com. Plus, you’ve gotta know the legal ins and outs of using AI-generated content. You must contribute significantly to the creation process to claim ownership, as evidenced in cases like Pannu v. Iolab Corp. Moreover, be mindful of potential lawsuits regarding unlicensed works, as seen in Andersen v. Stability AI et al, where artists faced challenges due to inadequate copyright protection.

Navigating the use of others’ IP requires ethical considerations. Whether you’re referencing creative works or likenesses in your creations, ensure they’re not derivative or infringing on someone else’s rights. Understanding the fair use doctrine is crucial, especially in cases involving AI-generated content. Recent legal battles, such as the photographer Lynn Goldsmith vs. the estate of Andy Warhol in 2023, underscore the complexities of IP in the digital age. By keeping your guard up and thinking ethically, you can keep your company’s rep intact while navigating the wild world of AI and IP.

Employee retention and acceptance

When it comes to employee retention and acceptance of AI in the workplace, it’s crucial to prioritize fairness and equity in AI systems. The quality and quantity of training data significantly impacts the performance of AI models, whether sourced through web scraping, public datasets, crowdsourcing, or synthetic data generation. While AI can mitigate human biases in decision-making processes, it’s essential to address representation bias and hiring bias, as seen in cases like Google Gemini and Amazon’s recruiting engine. By fostering a culture of collaboration with AI, organizations can ensure a supportive environment through education and training, encouraging experimentation, establishing feedback mechanisms, and addressing ethical considerations.

It’s crucial to address these ethical considerations and promote continuous learning and adaptation for AI to become an established member of the new world of business. Additionally, organizations should acknowledge and validate employee concerns and resistance to AI implementation, offering support and reassurance through opportunities for upskilling, reskilling, and career development. By prioritizing fairness, equity, and collaboration, organizations can harness the benefits of AI while fostering a positive and inclusive workplace culture.

Final thoughts and links to resources

AI is here to stay. So, let’s embrace the potential of AI while safeguarding against its risks, guiding our organizations toward a future where technology and humanity work hand in hand. If you want to learn more about the Dangers of AI for accountants, check out the Free Resources section of our website for this and other webinar playback links!

In addition, we share with you the resources that we shared with participations at our session. Enjoy!

AI Ethics: Navigating the New Frontier (Presentation)

AI Ethics: Navigating the New Frontier (Resource Document)