Hello,
I was attracted by the AI4good motivation but first 2 weeks of the course are rather generic and high-level with couple of interesting applications but introduced in low level of detail.
In my view, the presented lifecycle does not differ much from any prototypical technical project, new innovation or research case within or beyond ML. I’d recommend gaining the expertise from real projects in a profesional environment to get similar insights as the ones discussed in the course.
Nevertheless, I can observe couple of key differences in which AI4Good seems to focus more:
Explore and Design phases, that could take very long on purpose to follow the no-harm rule.
Being conservative about data, AI solution, whole end2end, privacy, security, impact on users, society, world, etc.
To me, this translates into longer duration of initial stages and longer project duration in general which seems to be in in the opposite direction of the agile dynamics of any business and the change rate of technology and stuff around the world. Then, AI4good is implicitly calling out for slow-like movements. It’s indeed a nice aim, but is it realizable in business or is it more for academia and non-for-profit research/innovation?
Does anybody sees other differences in the project lifecycle?
Hello @jyebes , as we all know AI4G is just a introductory course set to give learners idea how AI can be used in various fields for the benefit of the society overall. For a deeper dive you can check out the resources section .
Hi, @jyebes
Thank you for your kind feedback.
If you’re new to DeepLearning.AI, AI4G serves as an excellent introduction. However, to delve even deeper into the intricacies of the subject matter, there are a multitude of intermediate-level courses available for you to explore. Once you’ve successfully completed this course, I highly recommend considering these intermediate courses. They will provide you with an even more comprehensive understanding of the topics at hand, allowing you to delve into advanced concepts and further expand your knowledge in the field.
Thanks for your advice Abhinav. I’ll check more advanced courses as suggested.
Besides, coming back to my initial comment, what are the views from other experts on Applied AI, ML, AI4Good within short-term business targets? Beyond project/use case, enforcing AI4Good best practices seems to require longer timelines for design and analysis and investments more similar to longer research roadmaps rather than short-term industrial applications. I’ll be glad to get some views from other professionals and researchers.
Well, there are various perspectives to consider, but I personally believe that applied AI and ML can offer substantial benefits to businesses in the short term, depending on the specific challenges we aim to address. However, we must also take into account the social impact of our actions and be accountable to our customers and stakeholders, among other considerations.
While short-term projects can bring immediate advantages, I am of the opinion that long-term project lifecycle has the potential to deliver more efficient and practical solutions to society. As I learn more on AI, I have noticed an exponential growth in its development and potential. Striking a balance between short-term gains and long-term social impact is crucial.
Hope this helps.