Ensure equity in the impact of data science
Modern society is challenged by balancing the power of big data and its analysis with issues of privacy, equity, and safety. Safe use of data science includes making sure black-box solutions and machine learning methods also come with some certifiable guarantees that they will be unbiased, robust to uncertainties, and immune to deliberate attempts to compromise these properties. As data collection accelerates and use of data becomes increasingly tied to power and financial gain, WID data scientists are studying ways to ensure ethical and safe use of data that protect privacy and prevent bias.
A new era of data requires a fresh look at equity.
Much of WID's research contributes to the Data Equity Grand Challenge.
Explore WID news and discoveries:
New Tool Predicts Three-Dimensional Organization of Human Chromosomes
WID researchers have developed a computational tool that can accurately predict the three-dimensional interactions between regions of human chromosomes.
Continue Reading Next Gen Scientists Assemble in Madison to Bring Science to the Policy Table
The National Science Policy Symposium will take place at the Discovery Building and in Union South at the University of Wisconsin–Madison on Friday and Saturday, November 1 and 2.
Continue Reading Data Scientists Unite Research and Policy in New Project
A new data science project, "WEREWOLF", puts powerful modeling tools into the hands of Wisconsin policymakers to create the energy systems of tomorrow.
Continue Reading Fall ‘Crossroads’ Topics Include Trade Policy Models, Climate Change and More
The fall Crossroads of Ideas series kicks off in the Discovery Building on Tuesday, September 24 at 7:00 pm. WID researchers will be featured throughout the fall series.
Continue Reading New Faculty Bring New Possibilities to WID, UW
Claudia Solís-Lemus and Daniel Pimentel-Alarcón are experts in statistics and machine learning, augmenting WID's data science expertise.
Continue Reading Electronic Records Pin Broad Set of Health Risks on Genetic Premutation
WID graduate student Arezoo Movaghar was a collaborator in a study that employed machine learning to mine decades of electronic health records of nearly 20,000 individuals.
Continue Reading Our Grand Challenges
Keep the human brain healthy
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