At Eigen Systems, our approach to AI innovation is guided by a core set of principles
At Eigen Systems, our approach to AI innovation is guided by a core set of principles
Transparency
In absence of well motivated and documented actions relating to data ingestion, pre-processing, feature engineering and modeling, analytics pipelines will seldom behave as intended. We are committed to delivering cutting edge innovation to our customers that is contextualized within a catalog of meta-parameters and design decisions. An AI ‘flight envelope’ that lets customers know, leverage and repurpose our work
Fairness
A number of factors ranging from optimization methodology, variable selection approach, modeling assumptions as well as the underlying data generation mechanisms will cause statistical algorithms to be biased. We believe that AI algorithms that are deployed without a bias range-check, will frequently result in harm. We invest extensively in tooling and oversight processes that aim to a conservatively self-evaluate our algorithms for bias.
Accountability
We are accountable to our customers not just to deliver on our contractual commitments, but also to develop and sustain a high degree of trust in our delivery mechanisms. We actively seek criticism. When we have achieved a milestone in building our customers’ trust, we challenge ourselves to raise the bar slightly.
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