Unlike traditional professions that operate under clear legal and ethical codes, the tech world lacks a universally accepted rulebook. There is no global framework guiding what ethical technology should look like. Organizations like UNIDO have called for translating global considerations into concrete industrial standards, but such efforts remain aspirational. Voluntary guidelines from bodies like UNESCO and the OECD do exist—emphasizing ideals like safety, fairness, and trustworthiness—but they are not legally binding. As a result, accountability becomes fragmented. What one region or organization labels as “unethical tech” might be perfectly acceptable elsewhere. This inconsistency allows companies to cherry-pick which guidelines to follow, often opting for those that align with their interests rather than uphold broader ethical standards. In this uncertain legal landscape, the burden of responsibility often falls on individuals and communities to demand clarity and push for stronger, enforceable norms.

“Move fast and break things” – and face little consequences

The slogan “move fast and break things” has shaped the culture of the tech industry for years. But when systems fail or cause harm, who is left to deal with the consequences? In far too many cases, there are no meaningful legal consequences for unethical or irresponsible uses of technology. Companies often operate without being answerable to anyone! Not even to the communities affected by their tools and platforms. The Digital Rights Indicators reveal a troubling gap in accountability across the digital ecosystem.

Consider a few examples. In 2018, a self-driving Uber vehicle was involved in a fatal accident. Despite the tragedy, the corporation faced no formal liability. Facebook’s role in amplifying hate speech during the Myanmar crisis contributed to real-world violence, yet no executive was held responsible. Amazon’s experimental recruiting tool was found to systematically discriminate against women. The project was eventually abandoned, but not before quietly revealing how biased systems can shape real lives. These moments are not outliers. They point to a recurring pattern where harm is absorbed by the public, while those with the power to prevent it remain shielded.

The Illusion of Neutrality

One of the most persistent myths in the digital age is the idea that algorithms are neutral. This belief shapes how many people trust technology. Algorithms are often seen as purely logical, emotionless systems that simply process data and return results. Because of this, many assume that they are inherently fair. The mindset mirrors a familiar phrase—just as some claim that "guns don’t kill, people do," a similar logic is applied to technology: "algorithms don’t discriminate, humans do." This perception creates a dangerous gap in accountability. It allows companies to shift blame away from their systems and say, "it’s the algorithm’s fault," rather than taking responsibility for the outcomes those systems produce. But behind every algorithm is a series of choices—made by people, shaped by values, and driven by goals. Believing in the illusion of neutrality can prevent us from asking hard questions and demanding better answers.

Despite popular belief, technology is not neutral. Every system we interact with is shaped by human choices, social values, and historical patterns. Tools that appear objective on the surface often reflect the assumptions of those who create them. In fact, technologies are socially constructed. The data that fuels them and the decisions embedded in their design are influenced by cultural norms, economic priorities, and unequal power dynamics. As one scholar puts it, technologies “are neither objective nor neutral but outcomes of human deliberation and power struggles.” Reports such as the one from the National Institute of Standards and Technology have echoed this concern, showing how even statistical models carry built-in biases. These biases are not always intentional, but their effects are very real. Whether by accident or design, digital systems can reinforce inequality and legitimize existing power structures. When we talk about fairness in tech, we must look deeper to understand the layers of bias that shape what is built and how it is used.