Explore & Engage: Ethical People Analytics Practices

Are we born ethical, or do we learn it along the way? The nature versus nurture question has been around for a long time. I don’t claim to know the answer. But I do believe we can choose what we study, what we do, how we go about our work, and how we conduct ourselves. If you would like to build your people analytics ethics skills, here are some activities that can help along the way. 

Continuous Learning and Skill-Building: Ethical considerations in people analytics are ever-evolving. To stay informed and knowledgeable, you’ll want to ensure your self-development includes activities that will increase your knowledge and skills in being ethical:

• Learn from Ethical Thought Leaders: Do you have an ethical framework you fall back on? If not, set aside some of your self-development and study time to dive into different ethical frameworks that many philosophers have given a great deal of thought to like utilitarianism, deontology, and virtue ethics to find what resonates most with you. Or immerse yourself in the writings of ethical champions and thought leaders; you can find a long list of my favorite ethically forward books like Equality Machine, Invisible Women, or Weapons of Math Destruction at heatherwhiteman.com/pa-career-guide. 
• Follow Standards and Guidelines: You will also want to familiarize yourself with established ethical frameworks, such as the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems and the Belmont Report. And leverage those that are more specific to people analytics like the ISO 30439 Human Resource Management: Safe Handling of Data standard. Stay up to date on regulations; many of these are intended to preserve ethical practices so keeping up with evolving data privacy regulations (GDPR, CCPA, and HIPAA) as well as industry standards like ISO 27001 and the NIST Privacy Framework will help keep you ethical (and in compliance as a bonus).
• Learn From Examples: Analyze real-world examples and case studies of ethical breaches in data science and people analytics. What went wrong? What could have been done differently? Learning from others’ mistakes can help you avoid similar pitfalls.
• Participate in Ethics Training: Enroll in courses or workshops focused on ethics in data science and people analytics.

Create Your Own People Analytics Principles: Based on your values and the ethical frameworks that resonate with you, create a set of principles that will guide your work. These principles can be detailed or high-level, but try to have some way to tie them to actionable and specific practices so that they show up in your day-to-day work. Your ethics statement and principles should not just be documents; they should be a living part of your work. Use them to guide your decisions in every project. Here are some examples of ethics statements you might consider:

• I prioritize data privacy and security in all my projects.
• Fairness: I identify and mitigate biases in data, analyses, algorithms, communication, and decision-making to ensure fair and equitable outcomes.
• I am transparent about my data sources, methodologies, and limitations; I communicate my findings clearly and honestly.
• I carefully consider the potential impact of my work on others, both positive and negative.
• I take responsibility for the ethical implications of my work I am accountable for the impact my work may have on others.

Share your ethics statements or principles with trusted colleagues, mentors, or advisors and ask for their feedback. They may offer valuable insights and perspectives that you haven’t considered. Your ethics statement and principles are not set in stone and they need to be reviewed and revised regularly especially as you evolve your understanding of ethical issues and learn new best practices.

Take Your Technical Skills to the Next Level: As you build your analytical skills, focus specifically on learning the techniques and approaches that are best aligned with your ethical principles. For example, if you seek to be ethical by reducing bias, don’t simply build skills in data exploration – build skills in using data exploration techniques for bias detection. If you are learning how to build algorithms, learn also how to audit algorithms for bias using fairness metrics and testing methods, or by practicing on sample algorithms. Maybe you are hoping to learn some new types of analytical techniques – why not research and learn about data privacy-preserving techniques such as anonymization, aggregation, differential privacy, k-anonymity, l-diversity, or t-closeness? Or maybe you would like to get more knowledge about technology platforms – you could learn about data security best practices like access control, encryption, data masking, and regular security audits. As you work on your skills in data interpretation, you could focus on responsible data interpretation, learn to avoid overgeneralization and understand the limitations of data and analytical methods. If you are building your data visualization skills, you can master the creation of ethical data visualizations that accurately represent data without misleading your audience or skewing the results.

Assess Everything: Regularly assessing the ethical implications of your people analytics practices is a win-win. It not only helps identify and address potential issues proactively but also deepens your understanding of ethical considerations and strengthens your decision-making skills. I recommend assessing all of your people analytics work on things like privacy, impact, and legitimacy. 

• Privacy Assessments: These assessments systematically identify and mitigate potential risks to employee privacy. A thorough privacy assessment catalogs collected data, defines its purpose, verifies legal compliance, identifies potential risks (like breaches or re-identification), develops mitigation strategies (encryption, anonymization), reviews data security measures, outlines data sharing practices, and details employee communication plans, all while being regularly reviewed and updated.

• Legitimate Use Case Assessments: These assessments ensure data is used for valid and ethical purposes. They clearly articulate the business need, explore potential employee benefits, evaluate ethical implications, analyze alternatives, document the rationale, and involve stakeholder review. This process ensures data use is justified, responsible, and aligned with ethical principles.

• Impact Assessments: These assessments evaluate the potential consequences of people analytics initiatives on individuals and groups. They identify stakeholders, analyze potential positive and negative impacts (both direct and indirect, short and long-term), assess for fairness and potential discrimination, develop mitigation strategies, and establish monitoring and evaluation mechanisms along with feedback channels. This process ensures projects are implemented thoughtfully and considerately.