Who’s Making the Decisions? Understanding Algorithmic Bias in AI

Artificial Intelligence (AI) is becoming a major part of our everyday lives, deciding what videos we see, what products we buy, and even who gets a job interview. But what happens when those decisions are unfair? This article explores algorithmic bias in AI—how and why AI sometimes makes decisions that are not equal or inclusive. It aims to help students understand the issue, its real-world impact. Also, how they can play a part in creating more ethical technology in the future.

Artificial Intelligence and Algorithmic Bias

Artificial Intelligence is a branch of computer science that enables machines to learn from data and make decisions. AI uses one of its core tools, called an algorithm—a set of rules or steps that a computer follows. When we train algorithms with past data, they learn patterns. But if those patterns include human bias, the computer can copy and even worsen it. Therefore, this is called algorithmic bias.

Real-World Examples:

• Facial Recognition: Some facial recognition systems have difficulty accurately identifying people with darker skin tones because the training data included mostly images of lighter-skinned individuals. Thus, this can lead to higher rates of misidentification and discrimination.
• Hiring Algorithms: If a hiring algorithm is trained on data from a company where most past hires were men, it may favor male candidates. Unintentionally, perpetuating gender inequality in the workplace.
• Educational Tools: AI tools used in schools might rank students based on their postcode. Rather than their academic performance, it reinforces existing social and economic disparities.

These are not just computer mistakes. They are social problems built into technology. That’s why it is so important for diverse people to be part of designing AI. Understanding bias and ethics in tech helps ensure AI is not only smart but also fair.

The Importance of Diversity in AI

One of the most effective ways to combat algorithmic bias is to ensure that diverse perspectives are included in the design and development of AI systems. When teams are composed of people from different backgrounds, they are more likely to recognize and address potential biases in data and algorithms.

Ethics and fairness in AI are not just technical challenges—they are social responsibilities. By involving people from a variety of experiences, cultures, and identities, we can create technology that is not only intelligent but also just and inclusive.

Educational Opportunities

Students interested in AI and ethics can begin by studying subjects like mathematics, computer science, data science, and digital technologies. In high school, look for electives in coding or ICT (Information and Communication Technologies). Various online platforms offer beginner courses in machine learning, Python, and AI ethics.

Some excellent certifications and programs include:

• AI for Youth programs (offered by organizations like Intel or CBSE) introduce young learners to the basics of AI and its ethical implications.
• Google’s Machine Learning Crash Course provides hands-on experience with real-world AI problems.
• UNESCO’s AI and Ethics course (for schools) helps students understand the social impact of AI in educational settings.

University programs in Computer Science, Data Science, or AI often include modules on data ethics, human-computer interaction, and responsible AI design. Many institutions now offer interdisciplinary programs combining technology with social sciences to help students build well-rounded skills.

Career Path

A career in ethical AI and algorithmic fairness can lead to many exciting roles, including:

• AI Engineer – Designs and builds intelligent systems and applications.
• Data Scientist – Analyzes large datasets to uncover patterns and insights.
• AI Ethics Researcher – Studies the societal impact and ethical considerations of AI technologies.
• Human-Centered Designer – Ensures that technology meets the needs of diverse users.
• Policy Advisor in Tech – Helps governments and organizations develop regulations and guidelines for ethical AI.

Major employers include global tech firms like Google, Microsoft, Amazon, and local startups working in education, health, climate tech, and more. As awareness around ethical tech grows, so does the demand for professionals who can make AI fair and inclusive.

The Broader Impact: Why Algorithmic Bias Matters

Algorithmic bias is not just a technical glitch. Moreover, it can have serious consequences for individuals and society. Biased AI systems can reinforce stereotypes, deny opportunities, and even cause harm in areas such as criminal justice, healthcare, and education.

For example, if an AI tool used to assess creditworthiness is biased against certain groups, it could prevent deserving individuals from accessing loans or financial services. In healthcare, biased algorithms might result in unequal treatment recommendations for patients from different backgrounds.

Addressing algorithmic bias is essential for building trust in technology. Hence, ensuring that AI benefits everyone, not just a select few.

Conclusion

If you’re passionate about fairness, technology, and solving real-world problems, then exploring algorithmic bias in AI might be the path for you. Start by learning basic coding and reading about how AI works. Additionally, join a coding club or attend AI workshops. Most importantly, stay curious and ask bold questions like, is this fair?, who made this decision? and who’s missing from the data? Because the future of AI should be built by people who care not just about what computers can do, but what they should do.

References

1. Buolamwini, J., & Gebru, T. (2018, January 21). Gender Shades: Intersectional accuracy Disparities in commercial gender classification. PMLR. https://proceedings.mlr.press/v81/buolamwini18a.html
2. Huang, Y., Liu, W., Gao, W., Lu, X., Liang, X., Yang, Z., Li, H., Ma, L., & Tang, S. (2023). Algorithmic fairness in social context. BenchCouncil Transactions on Benchmarks Standards and Evaluations, 3(3), 100137. https://doi.org/10.1016/j.tbench.2023.100137

Additionally, to stay updated with the latest developments in STEM research, visit ENTECH Online. Basically, this is our digital magazine for science, technology, engineering, and mathematics. Furthermore, at ENTECH Online, you’ll find a wealth of information.

• Author
• Latest Posts

Dr. Ruwangi Fernando

Dr. Ruwangi Fernando is an award-winning AI scientist and Founder of STEM Sisters, an organisation dedicated to empowering women of colour in STEM. She is committed to advancing AI-driven innovation, fostering diversity in STEM, and shaping ethical and inclusive workforce solutions. She holds a PhD in Applied AI and has worked on projects ranging from traffic optimisation to bias-free recruitment platforms. Dr. Fernando is the 2025 Executive in Residence at Victoria University and a member of several national advisory groups on STEM equity and ethics.

You do not have any posts.