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Ethical dilemmas in computer science

In recent years, ethical issues in computer science such as hacking, data collection, and algorithmic bias have profoundly impacted our culture.
Written by Matthew Sweeney, Contributing Writer

If you are looking to pursue a career in computer science, you may have wondered what, if any, discussion exists around ethics in this field. The good news is that computer science ethics is an emerging area of discussion for STEM professionals and educators worldwide.

Let's say that emails leaked from an oil corporation reveal a pattern of leadership ignoring regulations meant to mitigate environmental impact. However, around the same time, the news reveals that these emails have reached the public thanks to hackers. Were the hackers' actions ethical, exactly? These and other concerns are current topics of discussion in computer science ethics.

Read on to learn more about the most common ethical issues in computer science, how they apply to computer science careers, and what we can learn from joining the discussion.

Why you should care about ethics in computer science

Ethics has become a paramount concern in computer science in recent years due to how our world has changed. As much of our lives has moved online and onto our devices, including more of our personal information, it has become more important for computer science professionals to behave with discretion and responsibility. 

Moreover, these concerns have become more pressing in light of how there are no independent accrediting bodies or boards with oversight over the tech field.

As a result, the typical computer science degree curriculum has adjusted to discuss the role of ethics in computer science professions. Computer science courses at the undergraduate, graduate, and postgraduate level often address or focus completely on cybersecurity ethics, intellectual property, or various other issues.

Real-life impacts 

One example of the importance of ethical software development is the story of Robert Julian-Borchak Williams, a Black man arrested in 2019 for a crime he did not commit due to faulty software. Facial recognition software used by Detroit police misidentified Williams as the suspect in a shoplifting case from 2018.

The misidentification occurred due to systemic bias underlying how facial recognition software is developed. The algorithms are trained largely on white faces and therefore may be less accurate at distinguishing between faces of people of color.

Ethical issues in computer science

The ethical issues faced by computer science professionals encompass many platforms, forms of technology, and client-professional relationships. Most of the problems they currently face relate to personal privacy, data security, systemic bias, or some combination thereof. For instance, hacking as an issue can potentially be an issue of personal privacy, even though the public mostly knows it as an issue of data security.

Read on to learn more about the five most prominent issues that CS professionals currently face in the modern world:

  • Hacking
  • Intellectual property
  • Privacy
  • Data collection
  • Algorithmic bias

Hacking

Hacking is the practice of exploiting vulnerabilities in digital security systems in order to unlawfully gain access to information. Hackers can pose a serious threat to companies, financial institutions, and even government agencies, especially when matters of national security are at risk.

"Ethical hacking" usually refers to the cybersecurity practice of testing digital security systems for vulnerabilities to find out how to fortify them better against hackers. However, some would even argue that illegal hacking can be used ethically to expose corporate or government corruption, such as in the case of the Panama Papers that were published to WikiLeaks starting in 2016.

Intellectual property

Intellectual property law presents a variety of ethical issues to the digital world. In the age of information, intellectual property has become murky. Many people regularly use the internet to share music and media freely, sometimes incorporating others' creations as part of their own.

This controversy also applies to computer science. Code and algorithms can be considered intellectual property, and using code or algorithms developed by others without giving credit pushes the boundaries of IP law and ethics.

Privacy

Ethical issues of privacy sometimes surface in computer science-related work. For instance, computer science professionals can access people's personal information and documents when called upon to make repairs to their devices. IT departments may sometimes be called upon to monitor employees' internet activity.

In these situations, computer science professionals need to exercise discretion and respect others' rights to personal privacy. For instance, it is unethical for a computer science professional to steal material from another person's hard drive for their own personal use.

Data collection 

Data collection has created additional ethical issues for computer science professionals. Many companies use digital consumer data to help make decisions and it is paramount that this data be collected in an ethical manner.

When data is collected and used without consent, such as in the case of 23andMe's selling of customers' genetic data, consumers feel a loss of trust. CS professionals can prevent this issue by asking for consent for data collection within digital consumer material and websites.

Algorithmic bias

Another emerging issue in computer science is algorithmic bias. Many laypeople make the incorrect assumption that technology is value-neutral, but algorithmic bias is an example of how technology can perpetuate human prejudice and inaccurate data.

Algorithms are only as smart as the data we train them on. If an algorithm is based on a dataset created with a racial, gender, or socioeconomic bias, its output will perpetuate the systemic bias shown in datasets used to train it. 

In conclusion

Joining the discussion on ethical issues in computer science offers many benefits. Being more informed on issues such as hacking and algorithmic bias can make it easier to change the culture of tech and make a difference in the world. If you're pursuing a computer science career or are completing a degree, consider researching how professionals practically deal with these issues.

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