At Okaya we are fully aware of the impact that our software can have on individuals, enterprises, and wellbeing professionals. We take this responsibility with deep commitment.
As our AI technology grows, we follow several principles that act as beacons in an ever-shifting and rapidly evolving technology landscape.

OKAYA PRINCIPLES

1. HUMANS FIRST

Okaya can have a large impact on its users. We view technology as a means to improve human’s decision making. An algorithm is not made to replace but rather to augment one’s ability to make better, more impactful choices.

 

2. HELP ALL HUMANS

Okaya actively works at preventing the introduction or propagation of bias against any group or individual. To do so, we carefully review the datasets we use to ensure they are as accurate and diverse as possible. We also strive to find better ways to monitor, detect and mitigate bias.
Our commitment transcends technology and into our hiring practices as we strive to bring team members diverse backgrounds, far-reaching knowledge, experiences, and perspectives to accurately represent the people Okaya serves.

 

3. MAKE BETTER DECISIONS FASTER

We focus on combining the strengths of computers with people’s life-experiences to improve and speed-up decision-making. We carefully craft Okaya to provide a clear understanding about our analysis and prediction, our confidence in the prediction and an accurate explanation of the data.
Okaya also has multiple feedback mechanisms to allow for human input so that humans and machines can strive together and make the world a better place.

 

4. PRIVACY AND DATA PROTECTION BY DESIGN

By default a user’s data is private and not shared with anyone.
We believe in opt-in rather than opt-out because people should be in control of what they share and with whom they share their personal data.
We incorporate privacy of data at each step of our process.

5. CONTINUOUS VALIDATION

Our algorithms are tested prior to use to validate both their output and to make sure we minimize the impact of bias.
Ongoing monitoring is performed to make sure that real-world results match the expected outcomes.

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