ImmerLearn

16/02/2020

National statistics play a critical role in creating a shared understanding between governments and citizens of how a society is doing. It was a privilege to contribute our perspective to how innovative data science solutions can increase the impact of national statistical offices and their products at the United Nations / OECD conference in Paris last month. Check out the talk of our CEO Wladimir Nikoluk on day 2 here:

https://paris21.org/news-center/events/PARIS21-UNSD-Conference-on-New-Approaches-to-Capacity-Development-for-Better-Data

04/01/2020

We're excited to have our CEO Wladimir Nikoluk join the PARIS21-UNSD Conference to discuss how national statistics and data can effectively improve the impact of public sector programs 🚀

Find out more about the event here: https://paris21.org/news-center/events/PARIS21-UNSD-Conference-on-New-Approaches-to-Capacity-Development-for-Better-Data

21/11/2019

Join us on Friday at 7pm (21 Nov) at the MPH Labs in Friedrichshain for a panel on Data Science for Entrepreneurial Changemakers!

Our CEO Wladimir Nikoluk will be talking about using data-science to help public and non-profit institutions measure their impact.

Tickets below!

Kairos Society invites you to join us in exploring how to use Data Science for Good.

16/11/2019

How do we use data, analytics, and technology to measure and manage impact? It was a pleasure discussing these questions with the Washington DC Global Shapers yesterday 🚀

10/11/2019

Photos of our talk at TEDxKassel are out! Check out this video here to learn more about how we are using machine learning for social impact :-)

https://www.youtube.com/watch?v=J3_LMr-JhwY&t

04/11/2019

We are excited to host our impact literacy workshop for the 2nd time with our partners from Fresh EBT and the World Economic Forum Global Shapers Community! Join us for a hands-on experience to become a smarter consumer of impact claims and know which questions to ask of your favorite impact-oriented organizations 🚀

Wladimir Nikoluk, Shaper from Berlin and CEO of Immerlearn, will lead a hands-on workshop to help participants assess impact claims.

21/10/2019

Internship opportunity with us in Berlin from mid-November 2019 to February 2020! We're a social enterprise that builds data science solutions for UN agencies, non-profits and impact investors to help them understand beneficiary needs, predict impact critical events and manage impact more efficiently.

We're looking for bright students or young professionals to support our data science and business development work. The position is paid. Don't hesitate to share and/or reach out directly to [email protected]

11/10/2019

Leo Tolstoy famously said that all happy families are alike and every unhappy family is unhappy in its own way. This rings true for social programs - they often tend to fail those who are most disadvantaged in the first place, who have particular needs, and who aren’t well served by standard approaches.

Machine Learning can help us build rich pictures of the individual needs of people. Used responsibly, this knowledge can help us deliver tailored social programs at scale and to meet individuals where they are.

Watch our CEO Wladimir Nikoluk present this idea at TEDxKassel:

After fleeing as a child from the chaos of post-Soviet Union Ukraine to Germany Wladimir and his family didn't have much. But a small library he discovered c...

18/09/2019

Meet our new intern, Bene, who helps us with business development in Berlin! On the one hand, this means building on our work in education and nutrition to find new organizations to work with. On the other hand, it means developing new data analytics solutions and getting feedback from potential users.

Right now, we’re thinking about new ways to use mobile phone data to help development agencies create transparency in areas with poor data availability.

As you can see from his hair, Bene loves to kitesurf. He also enjoys meditation, yoga, and hiking (he even runs a little hiking equipment rental platform on the side).

02/09/2019

In the 1970s, insurance companies and civil right groups debated the notion of 'actuarial fairness': whether people should pay insurance premiums based on their private risk profile, or whether insurance was about sharing risk. This debate had important ramifications for communities that were considered 'high-risk'.

Statistical models allow us to gain a more nuanced view of individuals, and make highly accurate personalised predictions. This gives us the technical capabilities to treat people very differently, and it raises ethical concerns about how we can still treat people fairly.

Thank you for the great discussion DOKUTECH, and check out this blog post to learn more about the topic! https://joi.ito.com/weblog/2019/04/28/2019-applied-et-1.html

09/08/2019

'Establish a new standard for social-sector decision-making' - Expectations vs. reality

Watch the video to see Wladimir Nikoluk speak about ImmerLearn at Harvard Kennedy School (https://youtu.be/t-LrEVw6-yE?t=34), and see our team working hard to develop a machine-learning model that predicts which students will need help, so that they can get the right support in time to complete their programs!