Beyond The Algorithm: 9 Helpful Tools To Put Ethical AI Into Practice

The MOOC is structured across three learning tracks, each designed to build understanding in a clear, accessible and engaging way. Channel leaders should evaluate AI vendors for ethical compliance and demand transparency in their models and data usage. EWeek has the latest technology news and analysis, buying guides, and product reviews for IT professionals and technology buyers. The site’s focus is on innovative solutions and covering in-depth technical content. EWeek stays on the cutting edge of technology news and IT trends through interviews and expert analysis. Gain insight from top innovators and thought leaders in the fields of IT, business, enterprise software, startups, and more.

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Organizations that prioritize education, security and continuous learning will be the ones that lead in the AI era. Generative AI ethics is an increasingly urgent issue for users, businesses, and regulators as the technology becomes both more mainstream and more powerful. AI is reshaping the channel industry, and ethical considerations cannot be an afterthought. Businesses that proactively implement responsible AI practices will not only mitigate risks but also strengthen their market positioning.

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In my colleague Dr. Gwen Nguyen’s GenAI for Teaching and Learning Toolkit, she offers strategies for integrating ethical reflection into course design not as a standalone lecture, but as part of how we explore and use GenAI with students. In addition, several players felt that even if the Little Droid cover art was human made, it nonetheless resembled AI-generated work. AI literacy should be both a training initiative and a policy-driven effort to ensure safe adoption.

The course is two weeks long and requires six to eight hours of work per week. It is designed primarily for business leaders, entrepreneurs, and other employees who are hoping to use AI effectively within their organization. The class is taught by a Cornell University professor of law and covers AI performance guarantees, the consequences of using AI, legal liability for AI outcomes, and how copyright laws specifically apply with AI.

Generative AI models consume massive amounts of energy very quickly, both as they’re being trained and as they handle user queries. Keep in mind this amount is just the emissions from one model during training on a GPU. As these models continue to grow in size, use cases, and sophistication, their environmental impact will surely increase if strong regulations aren’t put in place. Many of these tools also have little to no built-in cybersecurity protections and infrastructure. As a result, unless your organization is dedicated to protecting your chosen generative AI tools as part of your greater attack surface, the data you use in these tools could more easily be breached and compromised by a bad actor. Accountability is difficult to achieve with generative AI precisely because of how the technology works.

Beyond The Algorithm: 9 Helpful Tools To Put Ethical AI Into Practice

As the book highlights, key concerns include privacy, bias, environmental impact, and misuse of AI. Deepfakes, data leaks, and discriminatory algorithms can cause real harm if not addressed responsibly. Individuals must be careful about what data they share with AI tools, and organizations need guardrails to prevent misuse.

AI security risks and best practices will continue to shift, so training can’t be a one-and-done initiative. AI ethics has quickly become a popular topic in the legal field, especially as lawsuits related to intellectual property theft, data breaches, and more come to the fore. Current areas of focus for AI ethics in the legal system include AI liability, algorithmic accountability, IP rights, and support for employees whose careers are derailed by AI development.

The Future Of AI And Business Ethics

It aligns closely with UNESCO’s Readiness Assessment Methodology (RAM), a practical framework for assessing how prepared countries are, to implement ethical AI. Public access to information is a key component of UNESCO’s commitment to transparency and its accountability. AI models in cybersecurity and fraud detection can disproportionately flag individuals from certain demographics, leading to wrongful account suspensions or increased scrutiny without justification. AI-driven sales and marketing tools can create biased recommendations by prioritizing demographics that align with past buying behaviors, limiting opportunities for new markets and diverse customer bases. See the eWeek guide to the best generative AI certifications for a broad overview of the top courses covering this form of artificial intelligence. Although generative AI tools can be used to support cybersecurity efforts, they can also be jailbroken and/or used in ways that put security in jeopardy.

• As more AI regulations pass into law, standards for how to deal with each of these issues individually are likely to pass into law as well.
• Unfortunately, the growth of dubious content allows unscrupulous individuals to claim that video, audio or images exposing real wrongdoing are fake.
• As both individuals and as an organization, we continue to learn and build relationships as we actively respond to the Truth and Reconciliation Commission’s Calls to Action.
• Together, we can create space for thoughtful, values-aligned engagement with GenAI, one step, one question, one choice at a time.
• AI-driven sales and marketing tools can create biased recommendations by prioritizing demographics that align with past buying behaviors, limiting opportunities for new markets and diverse customer bases.

The core best practices for ethical use of generative AI focus on training employees, implementing data security procedures, continuously fact-checking an AI system’s output, and establishing acceptable use policies. Ultimately, these practices help students see that ethical engagement with AI isn’t a checklist—it’s an evolving mindset. They reinforce that learning, like technology, is not neutral, and that it is shaped by the values we bring to it. AI literacy programs should be ongoing, dynamic and delivered in frequent, digestible sessions. These types of bite-sized lessons with real-world examples and frequent updates will keep employees engaged.

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Through experience, education and practice, a practically wise person develops skills to judge well in life. Because they tend to avoid poor judgement, including excessive scepticism and naivete, the practically wise person is better able to flourish and do well by others. The need to exercise a balanced and fair sense of scepticism toward online material is becoming more urgent. In 2023, an Australian photographer was wrongly disqualified from a photo contest due to the erroneous judgement her entry was produced by artificial intelligence.