Equality before law in the age of Algorithmic Decision making : Author: Arjuman Lodhi
Artificial Intelligence is changing quickly the way government works the way people get jobs and the way legal systems operate.. There is a problem called algorithmic bias. This happens when AI systems treat some groups unfairly. This can be a worry for the idea of equality that is in the constitution. This paper looks at how AI might keep or make worse existing forms of unfair treatment. It focuses on the rules in the constitution that are in Articles 14 to 18. It talks about the need for openness, fairness and responsibility when AI makes decisions. The paper also suggests ways that the law, the constitution and the courts can help make sure that new technology does not harm equality and justice.
ARTICLE
Artificial Intelligence is changing quickly the way government works the way people get jobs and the way legal systems operate.. There is a problem called algorithmic bias. This happens when AI systems treat some groups unfairly. This can be a worry for the idea of equality that is in the constitution. This paper looks at how AI might keep or make worse existing forms of unfair treatment. It focuses on the rules in the constitution that are in Articles 14 to 18. It talks about the need for openness, fairness and responsibility when AI makes decisions. The paper also suggests ways that the law, the constitution and the courts can help make sure that new technology does not harm equality and justice.
Introduction
Imagine you are denied a loan or you are screened out of a job interview or you are flagged for checks at an airport and you never know that a computer program made the decision.
This is not a scenario. Government departments, banks and private platforms are increasingly handing over decisions that used to require judgment to algorithms.
The promise of these systems is speed and fairness. The danger is that these systems quietly copy and sometimes increase the bias that the Constitution was created to break.
In a democracy computers are quickly taking the place of human judgment. From choosing who gets a job to deciding prison sentences and giving credit scores smart machines are now part of areas where fairness is supposed to be the rule. But these smart machines are not naturally fair: they take on the unfairness of the people who make them and the information used to teach them.
Keywords
1. Algorithmic Decision-Making
2. Equality Before Law
3. Artificial Intelligence
4. Algorithmic Bias
1. Can Justice Hold Her Ground in the Age of Algorithms?
Imagine walking into a courtroom. You expect to see the symbols of justice: a blindfolded figure holding scales that represent fairness & a human judge who can listen understand the details of a person’s life & show mercy.
Now imagine a different scene. The gavel does not fall. Instead a server quietly works in a basement. A line of code scans your history your location your online activity & your past. In seconds it produces a number. That number may decide whether you get bail receive a loan get a job or are flagged as a threat.
2. Welcome to the age of Algorithmic Decision Making.
For centuries one of the main principles of society has been equality before law. This means that no matter who you are rich or poor powerful or powerless the law should treat you equally.
But when we give important decisions to machines we must ask an important question:
Can mathematics really be fair?
3. The Illusion of the Neutral Machine
We often trust computers without questioning them. When we see percentages risk scores & data we may think:
“Numbers do not lie.”
An algorithm does not appear to have personal feelings or emotions. It does not hate anyone & it does not get tired or angry. Because of this many people believe that algorithms can remove human bias & create a more equal system. But there is a problem. Algorithms do not exist separately from society. They are created using data & that data comes from our history.
Data can contain discrimination inequality & past mistakes. When we use this data to train a machine the machine may learn these patterns instead of learning what is actually fair.
It can repeat or even increase existing bias while making the decision look objective because it comes from mathematics.
4. When “Risk” Becomes a Proxy for Poverty
This problem can be seen in criminal justice & social welfare.
Risk assessment algorithms can be used to help make decisions about bail parole or sentencing. These systems may look at different “risk factors”. For example:
1. Where does the person live?
2. Do they have a job ?
3. How many times have they missed appointments?
These factors may appear neutral. But they can sometimes reflect a person’s economic & social background.
For example a person living in a poor area may be considered more risky simply because that area has higher crime rates or more police activity.
In such cases the system may not really be measuring future criminal behaviour. It may be measuring poverty & social disadvantage.
This creates a serious question:
Can equality before law exist if people are judged based on where they live or the conditions they were born into?
5. The Wall of the “Black Box”
Another major problem is transparency.
If a human judge makes a decision they usually have to explain their reasoning. A lawyer can question the decision & it can be challenged through an appeal.
But what happens when the decision comes from a complex algorithm?
Some algorithmic systems are owned by private companies. Their methods may be protected as trade secrets. This can make it difficult for people to understand why a particular decision was made.
If a person is labelled as “high risk” by an algorithm they may ask:
Why did the system make this decision?
If nobody can clearly explain the answer then how can that person challenge the decision?
How can someone defend themselves against a decision they cannot understand?
This is a serious challenge to equality & due process.
6. Bringing Humanity Back to the Code
This does not mean that technology is bad.
Technology can process huge amounts of information quickly. It can find patterns that humans may miss & it can sometimes reduce human errors. The problem begins when efficiency becomes more important than justice. To protect equality in the age of algorithms we need some important safeguards Transparency over Trade Secrets. If an algorithm is used by the government to make decisions that affect people’s lives there should be enough transparency to allow proper testing & legal challenge.
The data used by the system & the factors considered by it should be open to proper scrutiny.
7. Context Not Just Correlation
Machines mainly identify patterns. Humans can understand context.
Law must consider the whole situation not just numbers.
The Final Say Should Belong to a Human. Algorithms should assist humans rather than completely replace them.
A machine can calculate a score but a human should remain responsible for the final decision.
8. Epilogue: The Scale Needs a Heart
The blindfold of Justice represents the idea that the law should not care about a person’s wealth status or power.
But an algorithm can be blind in a different way. It may be unable to understand human circumstances context or personal change.
As we build our future with technology we must remember that justice is not simply a mathematical equation.
Equality before law is a human promise.
Technology can help us make better decisions but it should never replace human judgment where people’s rights freedom & dignity are at stake.
9. Case laws & Articles
Article 14 of the Indian Constitution guarantees equality before the law & equal protection of the laws to every person. It means that the State cannot treat people unfairly or discriminate arbitrarily.
In the age of algorithmic decision-making, Article 14 is important because algorithms used by governments or institutions must not produce biased, discriminatory or arbitrary outcomes.
1. E.P. Royappa v. State of Tamil Nadu (1974)
This case made it clear that arbitrariness has no place in equality under Article 14 of the Constitution.
It supports the argument that algorithms should not be allowed to make decisions that’re arbitrary or lack proper explanation.
2. Justice K.S. Puttaswamy v. Union of India (2017)
This judgment affirmed that privacy is a right and introduced the principle of proportionality. It is important when dealing with AI systems that collect and use data to make automated decisions.
3. Navtej Singh Johar, v. Union of India (2018)
This case reinforced the idea of equality and protected people from discrimination. It helps in showing how seemingly neutral algorithms can lead to unfair results if they treat people differently based on bias.
Conclusion
Algorithmic decision-making can make the legal system faster & more efficient but it also creates new risks of bias & unfairness. Technology should support justice not replace human judgment. Every person deserves a fair chance to understand & challenge a decision that affects their rights. The future of law should therefore combine the power of technology with human responsibility compassion & equality.
Sources & References
Research Gate - Algorithmic Bias & the Right to Equality: Reimagining Constitutional Guarantees in the Age of Artificial Intelligence.
Indian Kanoon- Constitution of India, Article 14 Equality Before Law & Equal Protection of law.
Supreme Court of India- Judgments relating to Article 14, equality, privacy & constitutional rights.
Live Law - Articles & case law analysis relating to Artificial Intelligence, algorithmic decision making & constitutional rights.
Legal Blur- Algorithmic Discrimination & Article 14