A team of researchers, engineers, and designers launched PerXAI in 2017 inspired by the global need to address rising information-uncertainty and general societal angst from the rapidly proliferating mis- and dis-information campaigns.

Our primary goal was to empower users to easily learn the true source and reliability of the content they were consuming. We knew we wanted to build a system from the ground up with a purposeful eye on how we created our products and built long-term trust with our customers. We set out to build the first privacy-first AI-assistant trained on your own data, with algorithms controlled by you.

We started by first articulating and codifying our Responsible AI Principles, which guided all of our design and engineering decisions.

1. Clearly articulate system optimization priorities (recall, precision, etc.)

  • Machine goals | human goals | business goals

  • Agreement on “noise"


2. Controls + familiarity

  • Balance predictability & serendipity

  • Build trust


3. Data is the outcome is the input.

  • Use the right training data: You are what you eat. You perform how you practice. (You get the idea.)

  • Give people control over their data.


4. Communicate consequences of actions and costs of failure

  • Define expected outcomes

  • Mitigation strategies

  • Edge cases (including emergencies)

  • Degrade gracefully

  • Train machine and person what and what not to ignore


5. Explain results

  • Communicate confidence

  • Suggest near-alternatives


6. Facilitate learning

  • Help users grow


7. Know what not to automate


8. Align to human needs

  • Understand your place in their workflow

  • Understand your place in the system


9.
 Demonstrate commitment to desired outcomes

PERXAI
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RESPONSIBLE AI