Ethical Use of AI: Finding Balance Between Innovation and Responsibility

Artificial intelligence (AI) holds immense revolutionary potential, making it remarkably popular in business application development. Even the most skeptical business leaders, who initially doubted AI's ability to outperform humans, are now embracing these technologies to keep up with market demands and stay competitive.

Yet, as AI adoption becomes more widespread, it starts raising ethical concerns. In this article, we'll explore the most significant issues and outline some core principles to help you navigate AI’s ethical risks. But first, let's take a quick look at the significance of AI adoption for modern businesses.

In 2023, global spending on AI-based systems hit $154 billion, according to Statista. This figure is impressive, but the adoption of AI is expected to soar even higher. The PWC’s Global AI Analysis Report predicts that by 2030, AI's impact on the global economy could skyrocket to $15.7 trillion. This growth will probably be fueled by increased labor productivity, product improvement, and stimulated consumer demand.

What do these numbers mean for your average business? Well, in whatever industry you operate, AI will most likely reshape or significantly influence it in the next 5 to 10 years. These trends are already taking root in today’s business landscape.

According to IBM’s Global AI Adoption Index 2023, 38% of IT professionals surveyed%20and%20France%20(26%25).) reported their companies actively using generative AI (e.g., ChatGPT-3), and 42% said they are exploring it. While generative AI is in the spotlight, AI's business applications extend far beyond that. According to a recent Forbes Advisor survey, the top three uses of AI in business include customer service (56%), cybersecurity (51%), and digital personal assistants (47%).

So, integrating AI into tailor-made software development projects is critical for businesses that strive to stay relevant, competitive, and profitable. But it's just as crucial to be aware of the ethical risks that come with AI adoption. Let’s explore them next.

AI differs significantly from other, more traditional technologies, raising numerous ethical issues regarding its use in business application development. Here are the major ones.

Privacy and data security risks

AI systems depend on data. They require it to learn, provide insights, and generate content. This maximizes the number of risks related to unauthorized access, data breaches, and privacy infringement:

• Corporate data protection. The data AI models use may include sensitive corporate information, making AI-based business systems tempting targets for cyber threats like hacking, malware, and adversarial attacks. 
• Individual privacy. AI systems frequently use personal data, especially for personalized services or medical insights. Collecting, storing, or using this data without consent can violate privacy rights.
• Group privacy (or algorithm bias). AI learns from the data it's trained on, which can lead to biases. Biased data may lead to stereotyping certain groups, jeopardizing their privacy, fairness, and equal treatment. This is particularly pertinent in such areas as hiring, lending, and law enforcement.

Privacy and data security concerns have sparked a few high-profile lawsuits against tech giants. Probably the most well-known case involves OpenAI and Microsoft. The plaintiffs claim that these companies unlawfully use the personal data of millions of internet users for their AI-based projects. The court has yet to decide if these accusations are grounded in facts.

Copyright violation

When incorporating generative AI into your tailor-made software development project, you should consider the potential risk of intellectual property rights violation. The data AI models use to create content may be copyrighted material owned by others. Consequently, AI-generated texts, images, and videos could potentially infringe on the original creators’ copyrights.

Copyright concerns have already led to several lawsuits. For example, The New York Times has sued OpenAI and Microsoft, alleging that these companies used its materials to train AI chatbots. Other AI companies, including Midjourney and Stability AI, have faced copyright lawsuits as well.

The black box problem

The black box problem means the difficulty in understanding how AI algorithms work and make decisions. Without this transparency, it’s impossible to ensure that AI algorithms are free from unfair, compromised, or discriminatory patterns. The black box problem is particularly worrying for the medical industry. Healthcare providers may not fully grasp how AI reaches its conclusions, which raises concerns about the reliability and accuracy of AI-driven medical recommendations.

For instance, in 2019, an AI-based healthcare risk-prediction algorithm was discovered to have racial bias. It assigned lower risk scores to black patients when determining which patients needed high-risk care management.

As you see, AI implementation is closely linked to ethical concerns. Can you take any action against it? Let’s discuss this next.

Ensuring the fully ethical use of AI in business application development and eliminating all possible concerns is certainly a challenge. However, the following guiding principles can help you minimize the risks:

• Transparency and explainability. This involves giving users a clear view of how AI systems work and make decisions.
• Accountability and human oversight. Humans should retain control over AI systems, clearly identifying who is responsible for their decisions.
• Fairness and equity. AI-based systems should be built in a way that avoids biases and discrimination.
• Privacy and data protection. AI systems must comply with data protection laws, ensuring that sensitive data, including personal information, is handled securely and responsibly.
• Safety and social impact. AI systems must be safe by design, not causing any harm either to individuals or society in general.
• Governance and collaboration. Industry players and governments should closely collaborate to ensure that AI ethical considerations are adequately addressed.

These rules might feel like a lot to handle. So, it might be best to team up with a trusted provider of custom software development services to recognize and address ethical AI risks in your particular project.

While AI might change the game across industries, offering numerous benefits such as increased productivity, efficiency, and quality, it also raises significant ethical concerns. Are data and privacy adequately protected? Is there any guarantee AI systems don’t violate someone else's intellectual property rights? Are AI algorithms fair and unbiased? These and similar questions stir up heated discussions in the business and tech world. However, you can mitigate ethical risks in your business application development project by adhering to the core principles of ethical AI use.