top of page
Search
Writer's picturePatty Beach

Building Consensus: Aligning Organizations for Ethical AI Adoption



In today’s world, everyone cares about ethics—but opinions on what’s “ethical” can vary widely. The challenge is defining ethics in a way that aligns with your organization’s unique values and serves your employees, stakeholders, clients, and community. As AI technology continues to evolve, we need to keep ethics at the forefront, ensuring that everyone in the organization is on the same page.


This post highlights a presentation I gave last week at the Organizational Development Network International Summit in Cleveland, Ohio. In it, we explored how leaders can establish ethical guidelines around AI, use Alignment to achieve buy-in, and take practical steps to implement AI responsibly.


Building an Ethical Framework with Consensus


Let’s face it: the concept of “ethics” can feel vague or subjective, and every organization has its own blend of people, values, and goals. When rolling out AI in a way that aligns with those values, it’s crucial to involve perspectives from across the organization to build a consensus. Create a cross-functional team with members from IT, HR, compliance, legal, and other areas to ensure that all voices are heard.


My own journey in aligning ethics and AI started with a commitment to making complex concepts simple and actionable. After years of organizational development (OD) work, I developed the Principles and Practices of Alignment to offer a structured, repeatable framework that engages people and builds alignment around shared goals. This framework now serves as a valuable approach for ethical AI adoption, ensuring that all parts of the organization are unified in their understanding and commitment.


Ethics Meets Technology: My AI Podcast Dilemma


Recently, our product manager used AI to generate a podcast episode based on my book, The Art of Alignment. It was impressive—two AI-generated voices discussing my book as if they’d read it and cared about it. But this raised ethical questions, as AI-generated voices don’t have personal investment and can’t give real endorsements.


Transparency is essential here. If I were to release that podcast without clarifying that it’s AI-generated, people could assume it was hosted by actual people. This experience reminded me of the importance of setting clear ethical guidelines as AI becomes more integrated into our work.


Lessons from Amazon’s Hiring Tool Misstep


Amazon provides another example of AI’s ethical challenges. They developed an AI hiring tool that was trained on resumes from the male-dominated tech industry, leading to biased recommendations that favored male candidates. This example underscores the importance of transparency and fairness in AI, as well as the need to scrutinize potential algorithmic biases. For AI to contribute to fair decision-making, we need to use diverse, balanced data and monitor the algorithms closely.


The Pillars of Ethical AI: Transparency, Fairness, and Privacy


When using AI, consider these key pillars:

  • Transparency: Make it clear when content or decisions are AI-generated. In the case of my AI podcast, for instance, transparency means letting people know it’s AI and not a real person.

  • Fairness: Regularly check your algorithms and data for any biases. A diverse team, including HR, IT, compliance, and DEI experts, can help identify and address fairness issues.

  • Privacy: Protect sensitive data, particularly when AI applications involve personal or confidential information. Robust privacy safeguards build trust and prevent unwanted leaks.


Shifting to an AHI Mindset: Augmented Human Intelligence


A concept my husband, Roger Toennis, developed has been transformative in our AI work: AHI, or Augmented Human Intelligence. Rather than viewing AI as a standalone decision-maker, we see it as a partner that enhances human insight. AI should help inform and support decisions, not replace the human touch. Keeping people in the loop with AI enables better decision-making and reduces the risk of unexpected outcomes.


Practical Steps for Ethical AI Implementation


Starting with ethical AI doesn’t have to be overwhelming. Here are some steps to get started:

  1. Get Leadership Buy-In: Having executives on board sets the ethical tone for the entire organization.

  2. Establish Cross-Functional Collaboration: Involve diverse departments—HR, IT, legal, and DEI—to ensure well-rounded decision-making.

  3. Employee Education: Not everyone understands AI, and that’s okay. Provide training so that employees know the ethical basics.

  4. Develop Clear Policies: Work with compliance and DEI teams to establish policies and standards around AI use.

  5. Integrate into Systems and Processes: Embed ethical AI principles into areas like hiring, performance evaluations, and organizational values.


Moving Forward with AI—Ethically and Inclusively


Ethical AI may seem complex, but it doesn’t have to be daunting. The Art of Alignment offers a structured framework to engage people and achieve alignment across departments. Rooting AI initiatives in inclusive leadership helps organizations benefit from AI responsibly and fosters a culture where technology serves organizational goals—not the other way around.


For more resources, check out my book, The Art of Alignment, and explore the Alignment Toolkit, which includes a cheat sheet and executive summary to help you create an ethical AI environment in your organization.


Thank you for joining me in exploring this essential topic. AI is here to stay, but with the right approach, we can integrate it into our workplaces in a way that’s ethical, inclusive, and aligned with our values.


Comments


bottom of page