Narmeen Haider

  • Student

Activity Feed

On November 14, 2018, Narmeen Haider commented on NYC BigApps: Crowdsourcing Civic Innovation :

Your piece raised a question for me: how do we ensure that everyone can contribute to open innovation? Given the rise in inequalities – particularly related to education – I’m worried that even open innovation will only attract a certain group of people: those who have the skills to innovate. Unless we can ensure that more people have these skills, including coding, we will not be able to get the range of solutions we are looking for. And in some ways this may increase inequality.

Interesting piece! As I read this, The Foundry almost seemed like a Venture Capital firm to me. Is Unilever best equipped to be a Venture Capital firm? Beyond investing, Unilever could leverage its experience and success with a variety of products to help startups with best practices – from marketing to distribution to manufacturing. Many startups struggle with these functions in the early days and would be willing to give up equity to get Unilevers support in these areas. They could also encourage innovation in emerging markets where innovators may not have the tools to bring their ideas to life.

On November 14, 2018, Narmeen Haider commented on Winsun: Revolutionizing the Construction Industry with 3D Printing :

Awesome article! A mobile 3D printer could increase access to housing in even the most remote areas of the world. 1.6 billion people—a fifth of the world’s population—will lack access to secure, adequate, and affordable housing by 2025. This technology could be game changing in reducing homelessness globally.

However, a big concern for me is how additive manufacturing will affect construction jobs. My assumption is that this technology will greatly reduce the number of workers needed per project, which means that many may not have jobs. Unless construction workers are given training in additional skills, they may not be able to work at all.

On November 14, 2018, Narmeen Haider commented on Hinge: A Data Driven Matchmaker :

Interesting read! The one thing I’d be interested in exploring is whether “Most Compatible” is biased based on race, ethnicity, etc. Dating apps always give me more South Asian men – even though I haven’t explicitly put that down as a preference. Also, as we learned from the TOM cases, the machine may pick up on biases from the person teaching it. I would hate for my dating life to be skewed based on someone else’s biases.

A big concern for me is cost and scope of access. Given that additive manufacturing is a relatively new technology, my guess is that it would cost a lot, which means that most healthcare systems would not be able to afford it. Additionally, even if it is materialized, very few people would be able to afford it. I am also unconvinced that the benefit of the technology would be groundbreaking/far-reaching. I would rather healthcare companies invest in technologies that will have greater reach and impact.

On November 14, 2018, Narmeen Haider commented on Can Machine Learning predict, prevent and diagnose Diabetes effectively? :

Per your second question, I think this is precisely the limitation of machine learning. While I agree that ML has a place in medicine – including in regulating diabetes – I don’t think it will ever fully replace provider interaction. The provider (e.g., nurse, physician, etc.) is able to look beyond the test results and really get to the root of the problem, whether that is physical, psychological, genetic, or something else. The provider can process unknowns, which is something machine learning is not able to do as of now. Furthermore, medicine changes quickly, and I’m skeptical whether machine learning will be able to keep up with the rapid changes.