Using this framework will help any Data Science team to deliver not only accurate models, but successful digital products generating true value for its users.
Is there anything you would add based on your experience? Drop it below!
Working in AI team is cool, but extracting value for a business from AI models is hard.
As a Data Scientist, Iโve seen many AI projects fail. The reason is usually that they aren't focused on value.
Hereโs a 5-step framework to turn every DS project into a $ generating machine:
5/ Interpretation:
Last but not least, spend time understanding why a model does what it does.
Users have trust in AI models in 2 cases: i) it is absolutely evident how it can help them or ii) they have an intuition of how it works.
i) is better, ii) is easier to guarantee
A research from Harvard Business School concluded that โOrganizations Routinely Fail To Realize The Full Potential From Their Data Science Effortsโ
Hereโs the 4 main reasons they have identified as root causes, and some possible solutions:
I totally agree with their research. Data Scientists need to step forward for AI to fully express its power both in the business sector and society alike.
I will publish a framework to tackle DS problems effectively tomorrow. Follow if you found the post useful!
@_r_figueiredo Absolutely. In tech, either you become a manager or you become a technical expert. In both cases you need to know how to deal with people, in addition to marketing your work
3. We're almost out (hopefully) of a bear market.
@Gartner_inc would say we are emerging from the trough of disillusionment in the technology lifecycle adoption. The moment has come to step up and make a difference. Being an early bird will pay off.
The opportunity is huge.