The discussion of ethics in business is nothing new, but with the advent and increasing adoption of AI, it’s developed an added level of complexity. If you login to social media, attend business conferences, or even speak with peers, you’ll encounter many businesses and individuals struggling to determine the most ethical use of AI.
If the ethics of using Artificial Intelligence is an issue your business faces, keep reading. We’re sharing the key components necessary for building a robust ethical framework for AI, as well as key areas where ethical AI practices are necessary for your business.
What is Ethical AI
AI software company C3 defines Ethical AI as “artificial intelligence that adheres to well-defined ethical guidelines regarding fundamental values, including such things as individual rights, privacy, non-discrimination, and non-manipulation.” They explain further that Ethical AI emphasizes the impact of AI on individuals, groups, and society as a whole while mitigating the risks that are inherent to AI (think inaccurate information, incoherent processes, etc.)
Although AI is a relatively new addition to common business practices, governing bodies have already begun to address the ethics of using it, creating regulations that ensure accuracy and fairness in its usage. Some of the most comprehensive approaches so far come from the Australian government and the United Nations Educational, Scientific, and Cultural Organization (UNESCO).
Australia’s AI Ethics Principles
For Australia, their principles for the ethical usage of AI are designed to complement, rather than substitute, existing AI legislation. The Australian government offers a deep dive into their AI ethics principles on their website. Here are the highlights:
Human, societal and environmental wellbeing: AI systems should benefit individuals, society and the environment.
Human-centered values: AI systems should respect human rights, diversity, and the autonomy of individuals.
Fairness: AI systems should be inclusive and accessible, and should not involve or result in unfair discrimination against individuals, communities or groups.
Privacy protection and security: AI systems should respect and uphold privacy rights and data protection, and ensure the security of data.
Reliability and safety: AI systems should reliably operate in accordance with their intended purpose.
Transparency and explainability: There should be transparency and responsible disclosure so people can understand when they are being significantly impacted by AI, and can find out when an AI system is engaging with them.
Contestability: When an AI system significantly impacts a person, community, group or environment, there should be a timely process to allow people to challenge the use or outcomes of the AI system.
Accountability: People responsible for the different phases of the AI system lifecycle should be identifiable and accountable for the outcomes of the AI systems, and human oversight of AI systems should be enabled.
Responsible Vs. Ethical AI
Ethical AI is often used interchangeably with the term “Responsible AI.” Although both address AI’s place in fair business processes, the two aren’t the same. Responsible AI makes it easy for businesses to scale using AI to develop systems that are human-centric, understandable, and transparent. Ethical AI, on the other hand, focuses on creating systems that are unbiased and open, but that may not always prioritize speed or efficiency.
Why is Ethical AI Important?
AI as a tool presents several dilemmas. Most importantly, it requires thousands of data points to even approach accuracy.
As a business owner, you’re already aware of just how important it is to protect customer privacy and what a show of trust it is for them to share their data in the first place. Not to mention the many laws to regulate the use, sale, and distribution of consumer data.
Using customer data to inform AI systems without transparency, trust, and ethics weaved into the framework runs the risk of not only running afoul of data privacy legislation, but also of ruining your brand reputation and hurting long-term growth and sales.
Some businesses might hesitate to adopt ethical AI practices due to concerns about cost, complexity, or potential slowdowns in operations. However, the long-term benefits far outweigh these concerns. Ethical AI can prevent costly legal issues, enhance brand reputation, and foster customer loyalty. Moreover, with the growing focus on ethics in AI, companies that adopt these practices early will be better positioned to compete in an increasingly regulated environment. By prioritizing ethics, businesses can ensure sustainable and responsible growth.
Potential Ethical Concerns of AI in Business
The ethical dilemmas of using AI don’t just impact one aspect of business; they extend throughout your entire organization. Each of these concerns can impact your business in different ways, from finding and retaining talent to long-term growth and marketing strategies. These are some of the most common ethical concerns you might encounter.
Unintentional AI Bias and Discrimination
One of the most significant ethical challenges in AI is the potential for bias. AI systems learn from data, and if that data contains biases, the AI can inadvertently perpetuate or even amplify them. For instance, an AI system trained on biased hiring data might favor certain demographics over others, leading to unfair hiring practices. To combat this, it’s important to use diverse and representative data sets and regularly audit AI systems for bias. Tools like IBM’s AI Fairness 360 can help identify and mitigate biases in AI models, ensuring that your AI-driven decisions are fair and equitable.
Data Privacy and Security
If you recall, AI takes a lot of data to learn and improve its accuracy. But where does that data come from? AI has already been shown to potentially violate consumer privacy and open their data up to leaks and identity theft.
Any business owner who uses AI in their business operations must ensure they have proper protocols in place to safely collect, use, and protect consumer data without violating their privacy rights. This includes data from social media, mobile devices, website interactions, and so forth. Without these protocols, the risk of customer data falling into the wrong hands increases.
Personalization
Personalization of consumer interactions with your brands aligns closely with the ethical risks of AI to data privacy and security. According to Forbes, 81% of customers prefer companies that offer personalized experiences, but that number decreases when there’s a lack of transparency and trust in the brand. Furthermore, privacy is the natural enemy of personalization, and with AI, that enmity becomes even more pronounced. Without transparency into how your brand uses AI, there’s a risk of violating consumer privacy and decreasing the number of consumers willing to share their data.
Let’s say, for instance, a couple wants to book a trip abroad using your brand, and your processes use AI to do so. Without clear explanations of how your AI helps the process, what data it requires to book the trip, and with whom the data is shared (both internally and with third parties), customers are less likely to feel comfortable with giving their information, and they’re less likely to book.
Inaccurate Reporting
Anytime a brand or individual uses AI, they run the risk of inaccurate reporting or misinformation. In the case of AI for research or writing purposes in particular, the systems have been shown to churn out inaccuracies, and in some cases, information that’s been completely made up. These inaccuracies show up between 4.8 percent and 26 percent of the time, depending on the statement category.
Copyright Infringement
As with all AI, generative AI tools like ChatGPT and Midjourney use data to learn and develop their content. Unfortunately, business owners have no way of knowing the copyrights attached to the images or pieces of content that these tools pull from. This can open businesses up to copyright concerns and legal matters they aren’t prepared for.
How to Ethically Use AI in Your Business
With so many potential pitfalls and concerns surrounding the use of AI, what can businesses do to ethically incorporate it into their operations? The answer is to build a robust ethical framework that addresses these important components:
Develop a Comprehensive Governance Model
Before you begin to incorporate AI into any parts of your business, be sure to develop a strong governance model that provides a template for ethical conduct that all employees and team members can easily follow. Intel’s internal governance model provides a great example of what that might look like. With it, Intel examines every action and use of AI through the lens of 7 principles:
respect human rights
enable human oversight
enable transparency and explainability
advance security, safety, and reliability
design for privacy
promote equity and inclusion
protect the environment
Real-World Examples of Ethical AI Implementation
Ethical AI is not just a theoretical concept but a practical approach that leading companies are embracing. In addition to Intel, several companies have already taken significant strides in incorporating ethical AI into their operations. For instance, IBM has developed AI Fairness 360, the open-source toolkit we mentioned earlier that helps developers identify and mitigate bias in AI models. Meanwhile, Microsoft has established the AI and Ethics in Engineering and Research (AETHER) Committee to oversee the ethical implications of AI technologies.
Incorporate Long-Term Monitoring and Evaluation
Implementing ethical AI is not a one-time task; it requires ongoing vigilance. Regularly monitoring and evaluating your AI systems ensures they continue to operate ethically as they evolve. Set up periodic audits and reviews of your AI models, and use monitoring tools to track their performance and impact over time. This continuous oversight helps catch any ethical issues early and allows for timely adjustments, keeping your AI aligned with your ethical framework.
Use Ethical Technology Tools
There are a number of tools available that support ethical AI. Model Cards, for instance, promote transparent documentation of AI model characteristics, helping brands track the ethics and efficacy of their AI usage.
Follow AI Regulations
Many industry leaders have begun working with regulators to establish consistent, enforceable standards for ethical AI practices. Although these standards aren’t yet enforceable worldwide, governing bodies like UNESCO and the Australian government have already begun to outline them. Similar to following the most comprehensive data privacy laws to ensure compliance, we recommend incorporating the principles for AI ethics into your AI practices.
Collaborate With External Stakeholders
Ethical AI isn’t just an internal matter; it’s a collaborative effort. Engaging with external stakeholders, such as industry regulators, ethical AI organizations, and even your customers, can enhance your approach. Consider joining industry groups that focus on AI ethics or obtaining certifications that demonstrate your commitment to ethical AI. For example, the Partnership on AI, founded by companies like Amazon, Google, and Facebook, is dedicated to ensuring that AI technologies are developed and used in ways that are beneficial to people and society.
Invest in Employee AI Education and Training
To ensure that ethical AI principles are fully integrated into your business, it’s crucial to educate and train your employees. This can include regular workshops, seminars, or online courses on ethical AI practices. Google, for example, provides internal training on fairness and ethics in AI to ensure that all employees understand the importance of responsible AI development and usage. Empowering your team with knowledge is a vital step toward a robust ethical AI framework.
The Business Benefits of Ethical AI Implementation
In addition to avoiding the ethical issues we outlined above, ethical AI implementation can have some serious benefits for your business. Here are some of the most notable benefits of ethical AI in business.
Builds Trust
We’ve said it before, but it bears repeating. Trust is the cornerstone of every working relationship. This applies to your brand’s relationship with customers as well. Collecting consumer data is an exercise in trust, processing or collecting that data for AI moreso. When you’re transparent about the data you’re collecting, what that data is used for, and how long you’ll use it, you build upon your relationship with customers and deepen their trust in your brand.
Mitigates Legal Risk
When you practice ethical and responsible AI, it reduces the risk of lawsuits and damage to your brand reputation. This extends from your reputation with customers through to your reputation with potential hires. AI is fallible, and its ability to present unbiased responses is limited by the bias of its programmers and the data it learns from.
Increases Customer Loyalty and Retention
Customers value transparency and relationships they can trust. When you demonstrate a commitment to ethical data use, whether it’s through AI or other means, customers take notice and reward your brand with their continued business and advocacy.
Start Addressing the Ethics of AI in Your Business
AI may be relatively new compared to other tools, but it’s here to stay. Whether you’re already using AI or are considering implementing it into your business, now is the time to take action. Conduct an AI ethics audit, set up an internal AI ethics committee, or start collaborating with external stakeholders to build a solid ethical foundation.
Moving forward, the ethics of artificial intelligence will continue to be a priority for consumers, organizations, and governments around the world. Those brands that adopt ethical and responsible AI practices now stand to benefit from being at the forefront of innovation and responsibility. Take the first step today by evaluating your current AI practices and identifying areas for improvement.
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