September 2016

Month

1. Crowdsourcing → Machine learning → Micro, macro policy evidence Premise uses a clever combination of machine learning and street-level human intelligence; their economic data helps organizations measure the impact of policy decisions at a micro and macro level. @premisedata recently closed a $50M US funding round. 2. Data blindness → Unfocused analytics → Poor...
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The driving force behind MDRC is a conviction that reliable evidence, well communicated, can make an important difference in social policy.” -Gordon L. Berlin, President, MDRC 1. Slice of the week: Can behavioral science improve the delivery of child support programs? Yes. Understanding how people respond to communications has improved outcomes. State programs supplemented heavy...
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analytics disconnected from strategy
1. Visualizing networks. @Polinode builds innovative tools for network analysis. One nifty feature allows creation of column charts using a set of nodes. A recent post explains how to use calculated network metrics such as centrality or betweenness. 2. Analytics are disconnected from strategic decisions. An extensive study suggests analytics sponsors are in the trough...
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Dentists will slow down on antibiotics if you show them a chart of their prescribing numbers.  Antimicrobial resistance is a serious public health concern. PLOS Medicine has published findings from an RCT studying whether quantitative feedback and intervention about prescribing patterns will reduce dentists’ antibiotic RXs. An intervention group prescribed substantially fewer antibiotics per 100...
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1. Panning for gold in the evidence stream. Patrick Lester introduces his new SSIR article by saying “With evidence-based policy, we need to acknowledge that some evidence is more valid than others. Pretending all evidence is equal will only preserve the status quo.” In Defining Evidence Down, the director of the Social Innovation Research Center...
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PepperSlice data-driven presentation
1. SPOTLIGHT: Warby Parker data scientist on creating data-driven organizations. What does it take to become a data-driven organization? “Far more than having big data or a crack team of unicorn data scientists, it requires establishing an effective, deeply ingrained data culture,” says Carl Anderson. In his recent O’Reilly book Creating a Data-Driven Organization, he...
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Museum musings.

Pondering the places where people interact with artificial intelligence: Collaboration on evidence-based decision-making, automation of data-driven processes, machine learning, things like that.

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