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Abstract Iceberg
Dark-Background

Algorithmic Bias Bountyâ„¢ Programs

Managed public and private algorithmic bounties

Icebergs

Unprecedented Velocity.
Global Impacts.

Companies are increasingly under pressure to address the issue of bias in automated decision systems but are unsure of how to publicly signal commitment to identifying and solving for inequity in experience on their platforms. 

 

The risks of introducing AI/ML to a company’s practice have shifted from only reputational to both reputational and compliance.

 

Global legislation increasingly mandates transparency and accountability in algorithmic systems, approved by third parties.

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We work with existing internal teams on risk detection and mitigation, infosec, and ML Ethics to institute a third-party approval process based on gold star standards, updated as these standards and laws are approved.

 

Working with our team ensures your products are globally compliant and your organization is clearly identifying and addressing ML biases.

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Abstract Iceberg

Increasing Public Demand for Responsible AI

McKinsey reports the following risks and urges companies to prioritize the following when it comes to AI:​ 

Cybersecurity, Compliance​, Explainability, & Personal Privacy

25%

Companies have experienced a  failure of AI

42%

Companies surveyed say Responsible AI top strategic Priority

$327B

Global Spend  on AI

in 2021

Juniper Research

230%

Spend growth between 2019-2023

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97M

AI Specialist deficit estimated by 2025

O'Reilly report

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