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What We Do
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Feasibility AssessmentMinimize risk, maximize results, and set your organization up for success.
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AI LabLeverage shared experience and collaboration to drive adoption and results.
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Catalog of OpportunitiesEmbark on your AI adoption journey with confidence.
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Generative AI WorkshopUncover innovative ways to engage with your data to shape your future.
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Featured
Navigating Bias in AI with Open-Source Toolkits
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Some Industries We Support
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Energy and ResourcesDrive innovation and promote sustainability while gaining a competitive edge.
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Financial ServicesBoost efficiency, reduce costs, and streamline processes.
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Forestry and AgriculturePave the way for a productive, efficient, and greener future.
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HealthRevolutionize care delivery, improve outcomes, and save lives.
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ManufacturingStreamline production, eliminate costly downtime, and enhance quality control.
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Featured
AltaML Secures Spot on AIFinTech100 for Consecutive Year
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What We Do
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Contact
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Featured
Jurisage and CiteRight Finalize Merger, Become Jurisage Group Inc.
Insights
AltaML’s Responsible AI Principles
Ethical AI Implementation
Responsible artificial intelligence (RAI) is non-negotiable. At AltaML, we are committed to implementing robust controls, adhering to established policies, and internal directives to ensure the ethical deployment of artificial intelligence (AI) technologies. Our mission is to elevate human potential with applied AI, and this mission is underpinned by a dedication to education and awareness.
Our guiding principles are as follows:
Inclusivity
Inclusive AI development aims to benefit people and the planet for the betterment of all. This is best achieved through diverse participation in the design and development of AI solutions.
Fairness
AI development must prioritize human-centered values, including rights, equality, fairness, and justice, with safeguards to mitigate bias.
Transparency and Explainability
Transparency in AI involves disclosing its usage and enabling understanding of its development, operation, and outcomes. It’s about providing explainability for users or affected parties.
Safety and Security
AI systems must serve legitimate purposes, prioritizing robustness and reliability to build trust while mitigating safety and security risks.
Accountability
Organizations and individuals must be clear on who is accountable for the outputs of AI systems. AI outcomes should be audited to prevent conflicts with human rights and environmental well-being.
Privacy and Data Protection
Privacy must be safeguarded throughout the AI life cycle. Collaboration is key to establishing data protection measures and adhering to privacy frameworks.
Awareness and Empowerment
Public trust in AI hinges on accessible education and expert guidance. Transparent communication helps foster understanding and empowerment ensures teams are encouraged to bring forward concerns about the usage of AI.