As AI becomes more deeply woven into business operations, the need for AI ethics policy to outline responsible AI use has become essential. Consider these recent, damaging examples of incorrectly implemented and unchecked AI:
- iTutor Group, an education company, settled a discrimination lawsuit for $365,000 after its AI recruiting tool unfairly rejected older applicants.
- In March 2024, entrepreneurs received legally unsound advice from Microsoft’s MyCity chatbot.
- Biased data in a 2023 AI system used by child welfare agencies led to disproportionate and mistaken targeting of low-income and minority families, which led to devastating consequences, including incurring of major debt and children being taken from parents.
As you’ll see in this article, the list of disasters goes on.
A new ethics imperative in business
AI systems don’t create bias. They mirror the data and parameters we feed them and reflect and potentially amplify existing biases it’s given. This reality played out in the examples above to show how crucial ethical AI guidelines are, yet there’s a striking disconnect in business today. Studies reveal that 73% of executives believe ethical AI guidelines are important, but only 6% have developed them. This gap between recognition and action creates risks that can severely affect people, destroy customer trust and business reputation.
Understanding responsible AI use
An AI ethics policy serves as your organisation’s framework for responsible AI use, establishing clear principles and practices that guide how you develop, deploy and use AI technologies. Without proper ethical AI guidelines as we’ve seen, the tech can inadvertently perpetuate biases or make discriminatory decisions. A strong ethics policy acknowledges this human element and requires a regular examination of both the training data and the assumptions built into any system a business implements.
Fairness, inclusion and transparency for optimal AI policy ethics
Consider a recruitment AI system that screens resumes. A strong AI ethics policy would require the AI to be trained in diverse candidate pools and regularly tested for bias. Take a marketing agency using AI for client targeting. AI might focus on one demographic if past campaign data shows it was most successful with that group. It’s not malicious; it’s a result of mathematical optimisation.
To ensure fairness, we must regularly audit our algorithms to uncover and fix any unintended exclusions stemming from our data and decisions. Ethics policies should specify how user customer data is used in AI training, who has access, and how it’s anonymised.
When using AI tools for process automation or decision support, teams should trace and understand the logic behind recommendations. This includes knowing which data points influenced the outcome and having clear channels to question or challenge results that seem incorrect or unfair.
Getting started with responsible AI use
Begin by charting AI’s presence across your business —from customer service to internal operations— to pinpoint ethical concerns and potential benefits. Next, assemble a team of leaders, technical experts, and customer representatives to create guidelines addressing practical challenges and concerns. Your AI ethics policy should address specific scenarios your business faces rather than generic statements.
Your ethical AI guidelines are far more significant than just a company document. It has the potential to become a powerful trust and accountability-building framework when your team uses it, ideally motivating them to champion ethics and challenge substandard processes.
Still unsure of how to proceed? The Oracle Tree team is here to support your business to access AI tools as part of our strategic business growth consulting service.
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