For AI to Work for Us, It Will Have to Stop Pretending to Be Us

• AI is not neutral; it actively reproduces existing patriarchal and colonial power structures and biases present in its training data.
• Tech companies prioritize business models and profit over human rights, frequently reducing human lives to data points and disposable inputs.
• AI cannot replicate human empathy, lived experience, or moral responsibility; attempts to simulate these qualities devalue human connection.
• A human rights-based approach requires moving beyond the myth of technological inevitability to hold power accountable for the societal impacts of their products.

The Myth of Neutrality

• AI models scrape vast amounts of data that contain historical exclusions, racism, and inequality, which the system then encodes and amplifies.
• Corporate incentives drive the deployment of advanced AI without adequate understanding of the consequences, impacting land, resources, and ecological health.
• In military or policing contexts, the algorithmic reduction of human beings to targets or success rates facilitates the justification of harm and dehumanization.

Why AI Cannot Replace Humans

• AI operations are based on statistical probability and pattern recognition, which lacks the context, care, and accountability inherent in human relationships.
• Treating machine-generated outputs as equivalent to human interaction erodes the value of community, empathy, and collective resistance.
• The narrative that AI replaces humans is a dangerous framing that enables the systemic disposability of people in sectors like welfare, health care, and hiring.

Demanding Accountability

• The burden of mitigating AI harm should not fall on those with the least power; accountability must rest with the entities building and deploying the technology.
• We must interrogate the design of these systems at the point of commercialization, asking who benefits and what values are being prioritized.
• Future development should be centered on the needs of living beings rather than optimizing systems for corporate growth and mechanical efficiency.