Michal Nachmany: using open-source to achieve climate justice
Michal Nachmany joins Craig Turner to talk global climate policies, plus how to help the world’s largest emitters make better policy decisions with Climate Policy Radar.
Michal Nachmany joins Craig Turner to talk global climate policies, plus how to help the world’s largest emitters make better policy decisions with Climate Policy Radar.
Michal Nachmany has dedicated over 12 years of her life to the fighting the global climate crisis. In 2021, Michal set up Climate Policy Radar. A not-for-profit, open data startup leveraging the latest in machine learning and NLP technology to build the world’s first global database of climate policy and legislation.
In episode five of the Founders For Good Podcast, Michal joins Craig Turner to talk global climate policies, plus how to help the world’s largest emitters make better policy decisions.
Keep reading to discover...
📊 What the issues are with the current data used to make policy decisions
đź’» How technology can accelerate the mapping of global climate policies
🙌🏾 Why open-source and not-for-profit is the best way to achieve climate justice
Michal: I think witnessing and being hands on in the policy making process, you get how anecdotal and siloed these processes can be. You know, you hire a consultant, you went to a conference and heard about three great examples, etc. Â
Often people in the policy making world just don't have enough time and background. Alot of them are generalists and need to make quick decisions, then the political layer is slapped on top of that, and you need to make it okay for everyone. So, it's a really complex world. Â
We're not going to solve the political problems immediately, but by providing people with clear and rigorous information about their policy options and the likelihood of these policy options to actually yield results, then potentially we can improve some things.
Good data doesn't necessarily lead to good decisions, but bad data necessarily leads to bad decisions. I think that's what we need to remember.
Michal: The LSC wrote a little booklet of climate laws in 16 countries and continued writing that as an annual publication. I joined and then led the project and brought it to cover all 200 governments in the world.
It was a compendium of all the laws and policies that all those governments have passed or enacted. That became a resource that today has about a quarter of a million users globally. These users range from UN agencies to investors, to companies, to academics, to journalists who need information about the laws and policies that exist.
It's a fantastic project and I'm proud to have to have led it, but it was coming to its natural limits because it was in an academic, social sciences university that mainly relied on extremely capable research assistants going to countries' websites or setting up Google alerts and finding out what those laws were. That's really slow and cumbersome and we couldn't get to the deep insights that we needed. Â
We live in an era where big data, machine learning models and natural language processing are exploding. Especially in the last five years where we've really seen a revolution in how natural language processing allows us to digest huge quantities of data. The question is, why are we stuck with Googling Angola's climate policy when we can do something a little more elegant than that?
I then left LSC and founded Climate Policy Radar, which aims to marry this world of need with all of the hundreds of thousands of users who are hungry for data about climate policy with technology that will allow us to do it better and faster and deeper and generate insights.
Michal: The climate crisis is not waiting for us. The climate crisis requires swift action and swift action is enabled by collaboration. Open-source, in my opinion, is the fastest way to achieve that collaboration.
It's also the safest way to ensure that your models are not biased. A lot is at stake if our models provide data that say this is the right way to go, we really need those models to be non-biased. Because we have a global approach, whatever works for Germany might not really work for Bangladesh. Whatever terms are used in policy making in Argentina might be used in China very differently. Making sure that we're not creating a bias towards anything really requires open-source. Â
Why not-for-profit? We know that there's a lot of companies that make a lot of profit from open-source, right? There are great models for that. But for the climate crisis, the people who need this data are the ones who are least able to pay for it. The people who are harmed most by the consequences of climate change are the ones who are the least resourced. Those are the ones who need it.
So there's a really strong angle of climate justice here. Of providing this to those who need it the most, who are harmed most by the ridiculous growth that we've had - the disproportional growth to our capacities. And this is our attempt of providing a public good because we believe that anything that is used for fighting rising emissions and extreme weather events and rising sea levels is something that should be a global public good, and therefore available for free for all. Â
Want to learn more about Michal’s journey with Climate Policy Radar? Listen to episode 5 of the Founders For Good Podcast.‍
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