Do You Have a Right to an Explanation?
Understanding AI Decision Transparency (Explainable AI)
Artificial intelligence now shapes many high-stakes moments in everyday life. A résumé may be screened by an algorithm, a loan application may be scored automatically, and medical teams may rely on AI-assisted image analysis and triage. If AI influences outcomes that affect your career, health, or access to financial services, you should be able to understand why a decision was made.
The “black box” problem
Many modern AI systems are complex and opaque. People often receive a rejection or approval with little or no reasoning. Well-known incidents—such as unexplained credit-limit disparities and biased hiring tools—show how lack of transparency can erode trust and expose organizations to legal and reputational risk.
The right to an explanation: legal landscape
GDPR (EU) – Individuals have rights related to automated decision-making, including access to meaningful information about the logic involved and the significance and envisaged consequences of such processing. These are not mere notices; they allow people to understand and challenge AI-driven outcomes.
EU AI Act – Classifies AI systems by risk and imposes heightened obligations for high-risk uses such as hiring, healthcare, and law enforcement, including documentation, transparency, and human oversight.
United States (state level) – Privacy and AI-focused laws in states such as California and New York are moving toward greater transparency, accountability, and anti-discrimination in automated decision systems, especially where decisions materially affect individuals.
Why transparent (explainable) AI matters
Trust – Users and regulators are more likely to accept AI outcomes when the rationale is understandable.
Fairness – Explanations enable detection and remediation of bias against protected groups.
Continuous improvement – Clear reasoning and error analysis help teams diagnose failures and improve models.
Global business obligations (high level)
Organizations deploying AI that affects people’s rights or opportunities should be prepared to:
Disclose when automated decision-making is used and why.
Provide advance notice and a clear explanation, upon request, of key inputs and reasoning.
Offer a way to contest decisions and obtain human review.
Maintain documentation, testing, and governance to monitor accuracy, bias, and drift.
Align practices with applicable laws where users live (EU, UK, U.S. states, etc.).
Practical tips
For individuals
Ask whether an AI system was used in your hiring, lending, insurance, or service decision.
Request an explanation of the key factors and how they were weighed.
If you suspect error or bias, submit a written objection and ask for human review.
For organizations
Map where AI influences outcomes; classify uses by risk.
Give clear notices and concise explanations that a layperson can understand.
Keep records of data sources, model versioning, testing, and monitoring.
Conduct regular bias and impact assessments; document remediation steps.
Ensure a meaningful human-in-the-loop escalation path.
If you need help designing explainable AI workflows, drafting notices and contestation procedures, or aligning with the GDPR, the EU AI Act, and evolving U.S. state requirements, LexSoy can assist. Contact contact@lexsoy.com for tailored guidance.
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