The Good Tech Companies - Algorithms are All Around Us, but Can They Be Trusted to Govern Us?

Episode Date: March 6, 2025

This story was originally published on HackerNoon at: https://hackernoon.com/algorithms-are-all-around-us-but-can-they-be-trusted-to-govern-us. An algorithm can take over the world! But we still can take over some decentralized algorithms, especially the ones in crypto. Check more stories related to web3 at: https://hackernoon.com/c/web3. You can also check exclusive content about #decentralization, #algocracy, #data-structures-and-algorithms, #tyranny-fascism-and-technology, #decentralized-governance, #obyte, #good-company, #hackernoon-top-story, and more. This story was written by: @obyte. Learn more about this writer by checking @obyte's about page, and for more stories, please visit hackernoon.com. Algorithms are being used by individuals, companies, and governments to make decisions already. Algorithms increase efficiency and reduce human participation, but they can become dystopian as well. These systems analyze personal data to predict behavior without people realizing it.

This audio is presented by Hacker Noon, where anyone can learn anything about any technology. Algorithms are all around us, but can they be trusted to govern us? By obit. Algochrissy, government by algorithm, or, algorithmic regulation, isn't exactly a well-defined or clear concept. However, we can sum it up like this. Algorithms plus governance, laws or rules of some kind. In this sense, we can talk of AlgoCrisis when some type of algorithm-based system, be it a smart contract, an artificial intelligence, I, or any other, controls, fully or partially, the decision-making processes of some platform, project, venture, or institution. It's very much not the same as e-government, governments using digital tools,

and it poses its own set of potential issues. An algorithm is more than just a simple digital application, it is a structured set of precise instructions designed to tackle complex problems, while also having the potential to create new ones. In the novel Demon, 2006, by Daniel Suarez, for instance, we can see how an algorithm takes over the world secretly, even murdering people, for instance, we can see how an algorithm takes over the world secretly, even murdering people, after ITS creator passes away.

We haven't reached such a dystopian level in our own world, but we might be building the path for it. Algorithms are being used by individuals, companies, and governments to make decisions already. And important decisions, at that. Algorithms in action. If you've been wondering. Yes, cryptocurrencies work with algorithms.

Smart contracts work with algorithms, and entire crypto networks are built on algorithms. They use these complex, mathematical instructions to replace expensive or distrustful human middlemen in verifying transactions. Algorithms also help people make general decisions about their platforms by providing the infrastructure for them to vote on chain governance in crypto networks. thesis just a couple of examples of what algorithms do, but that's far from all they are up to. In 2017, the police from Durham, UK, introduced the Harm Assessment Risk Tool, HART, an AI system that predicts the likelihood of a suspect reoffending.

It classified individuals into risk categories, helping to decide whether they were detained or eligible for rehabilitation. Similar predictive policing methods, often powered by machine learning and data analysis, are used in the US and China. Smart cities provide another real-world application of algorithmic governance. AI-powered infrastructure, such as intelligent street lighting and automated traffic systems, optimises resource use. Projects like the futuristic city, the line, in Saudi Arabia are planning to integrate AI for proactive services. Governments are also incorporating AI in decision-making, from automating tax audits to using predictive models for social services.

AI judges, tested in China and Estonia, can handle minor legal disputes, while predictive algorithms assist in judicial sentencing. Education sees similar automation with platforms like Newton, which adjusts learning materials based on student performance. Language models like Chad GPT or DeepSeek are built on algorithms. Language models like Chad GPT or DeepSeek are built on algorithms. Google Sir chooses algorithms to rank results. YouTube, Netflix, and Spotify use algorithms to suggest personalized content, and Amazon does it to customize shopping suggestions. Algorithms are useful, and we're already surrounded by them. Dystopian algorithms. Algorithms increase efficiency and reduce human participation, but they can become dystopian

as well. One major concern is what Evgeny Morozov called, invisible barbed wire. A system where algorithms subtly guide choices, restricting intellectual and social growth without people realizing it. These systems analyze personal data to predict behavior, nudging individuals towards certain actions while limiting exposure to alternative ideas or opportunities. Since the constraints aren't explicit, people assume they are acting freely, even though their options have been carefully curated by unseen forces.

This quiet control can weaken freedom by reducing critical thinking and reinforcing pre-existing habits instead of fostering independent decision-making. In other words, people mindlessly follow suggestions from the algorithm, not knowing how the algorithm works, unaware that they might be manipulated, but afraid of taking alternative paths that could harm them. The opacity of these decision-making systems is another pressing issue, indeed. Many algorithms function as black boxes, making critical choices without clear explanations. This lack of transparency is dangerous, especially when algorithms are aid-trained on biased data.

If an algorithm unknowingly reflects historical inequalities, it can perpetuate discrimination while presenting its decisions as objective. For instance, predictive policing tools have been criticized for unfairly targeting marginalized communities, and eye-driven credit-scoring systems have disproportionately disadvantaged certain groups. When these tools shape financial access, law enforcement, and employment, the risks of biased automation become significant. Some bad history, real-world examples illustrate the harm poorly designed algorithms can cause. In 2018, the Dutch government deployed the algorithmic system SYRI to identify potential welfare fraudsters, flagging thousands of people for investigation without clear justification. Public backlash led to the

system being shut down in 2020 for violating human rights. Similarly, in 2021 in the US, Atlas software was used to evaluate immigration applications, drawing criticism for its opaque and potentially discriminatory decisions, and its ultimate goal to denaturalize citizens. In the UK, an algorithm assigned student exam grades in 2020, favoring those from wealthier schools while penalizing others. Widespread protests forced the government to reverse the decision, demonstrating how unchecked algorithmic control can directly impact lives.

https://www.youtube.com.watch?v="re-yjx5exh0-an-embeddable-equals-true-while-algorithms-can-streamline-decision-making, their misuse can entrench systemic issues, limit freedom, and erode trust. Without transparency, accountability, and ethical oversight, centralized algorithms risk becoming tools of control rather than empowerment. Decentralized justice. So far, at least, we can say that the most tyrannical algorithms come from the centralized world. It's always a central party, company or government, controlling the whole thing to reach their own dubious purposes, or messing stuff up for mere negligence. Luckily for us, algorithms can still be used to bid freedom and justice, especially if

they're decentralized. As you may be guessing, most crypto algorithms are open source and decentralized, available for everyone to check and use. And we already have some algorithmic systems for decentralized justice. A key element in decentralized governance, for instance, is the Decentralized Autonomous Organization, DAO, which operates using smart contracts, self-executing agreements. DAOs allow members to participate in decision-making through voting, ensuring that control is distributed among participants rather than a central entity.

This is a type of on-chain governance, where rules and decisions are executed through DLT-verified processes, and it helps maintain transparency and security while preventing manipulation by powerful individuals or organizations. Decentralized justice aims to resolve disputes fairly and efficiently while avoiding the risks of centralized control. Traditional courts rely on human judgment, but decentralized justice systems use crypto-economic incentives to ensure impartiality. Participants are rewarded for aligning with the consensus, which is assumed to be fair

decision-making. This method eliminates reliance on trust and instead uses incentives to ensure just outcomes. Additionally, decentralized justice is designed to be transparent, with rules and decision-making processes openly available on the network. This guarantees predictability, consistency, and resistance to bias or corruption. Algochre C for Good, an apt algorithmic network to build fairer justice systems is Obite, a fully decentralized ledger technology, DLT, that removes intermediaries like miners and, validators. Obite also enables on-chain governance, allowing its community to make

key decisions collectively through voting mechanisms. It also supports smart contracts, which automate transactions and agreements without requiring a central authority. Additionally, Obyte offers contracts with arbitration, allowing parties to engage in agreements where disputes can be settled by using not only smart contracts but professional human arbitrators from the ARB store. These features ensure that transactions and governance remain transparent, fair, and resistant to external control, reinforcing the principles of decentralization in both governance and justice. It's also a great example of how to use the Algochrccy for good, featured vector image

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