Machine learning impacts so many parts of our daily lives, whether it’s doing a Google search, using your smart watch, or getting movie recommendations. Healthcare providers and businesses are using it to gain insights to guide decision making. And it’s also being applied to solve some of the world’s toughest problems like climate change and food security. Several recent WiDS talks, workshops, and podcasts describe the exciting applications of machine learning today and offer skills development workshops for new and experienced data scientists.

Lesly Zerna, investigadora, docente, mentora, creadora de contenido y desarrolladora de software boliviana, comparte su pasión por aprender y enseñar ciencia de datos e inteligencia artificial. Ella dice que el aprendizaje funciona mejor cuando conoces tu estilo de aprendizaje personal y lo aplicas a los temas prácticos que te interesan. 

​AI and machine learning are increasingly being used across industry and government to make decisions impacting many parts of our lives. These technologies could determine who gets a job interview, what products are advertised to different audiences, or what government resources are allocated to different populations. Bias can become embedded in the development of AI systems either through the data and/or the development and evaluation of algorithms. This can result in inaccurate predictions that can significantly impact people’s lives. Several WiDS talks describe how bias in machine learning can impact everything from online ads to search recommendations to bus routes.

​Leda Braga is founder and CEO of Systematica Investments, a hedge fund known for using data science-driven models to support its investment strategies. On the WiDS Podcast she explains how systematic investment management is data science applied to investment and how she believes it is the future of the financial industry.

Jessica Bohórquez, investigadora de la Universidad de Adelaide en Australia y consultora de la industria, está utilizando IA y transitorios de presión para inspeccionar y monitorear tuberías de agua para detectar fugas. Ella habla sobre su doctorado, su trabajo en la industria y sus consejos para seguir una carrera en ciencia de datos.

​Dr. Karolina Urbanska, a data scientist working for Teach First in the UK, has spent her career using data science to better understand human behavior. On a new WiDS Podcast episode whe discusses her work as a data science and psychology researcher, her decision to leave academia, and her learnings along the way.

​The pandemic has changed the way that people think about their lives, and their work. A recent survey conducted by Gartner suggests that instead of using the term ‘great resignation’, organizations need to think about the ‘great reflection’, as employees are seeking more purpose in their work.

​WiDS Co-Founder Margot Gerritsen welcomes her new podcast co-host Cindy Orozco, as they interview each other on a new WiDS Podcast episode about their career paths to data science, coping with the imposter syndrome, and successfully juggling busy lives.

Financial services is an industry built on data and not surprisingly data science plays a pivotal role in helping financial firms assess risk, detect fraud, make profitable decisions, and improve the customer experience. The Women in Data Science (WiDS) Conference and podcast series shares the perspectives of leading experts on the vital role of data science in financial services.

​Tahu Kukutai, a professor at the University of Waikato in New Zealand and a Māori woman, is leading data sovereignty initiatives that advocate for indigenous data ownership, guardianship, and governance. On a new WiDS Podcast episode Tahu delves into indigenous data sovereignty, as she walks us through her experiences and initiatives.

Allison Koenecke, currently a postdoc at Microsoft Research and soon to be assistant professor at Cornell, discusses her decision to pursue a career in academia focused on algorithmic fairness and causal inference in public health, on a recent WiDS Podcast episode.

Karina Edmonds, Global Head of Academies and University Alliances at SAP, has spent her career building bridges between business and academia. On the WiDS Podcast she talks about her passion about promoting fairness in data science by bringing more young people, women, and underrepresented groups into the field.

We live in an era of big data with data sets that require computational analysis to gain insights and knowledge. The volume of big data has been increasing steadily, and will only continue to climb. Since we started the WiDS initiative in 2015, Statistica estimates that the volume of data has increased from 15.5 to 74 zetabytes, and they forecast that data volume will double again by 2024.

Yet with all of this data, one of the biggest challenges that data scientists and researchers face is dealing with missing data. In some cases, the missing data is due to not readily having access to the data sets that are required to perform the analysis, while other cases involve data sets that are incomplete and not uniformly populated.

​Fatima Abu Salem, a professor at the American University of Beirut, talks about how the conflict in the region has shaped her life journey and motivates her to apply data science for the public good to address challenges in Lebanon, on a recent WiDS Podcast episode.

Data science is being applied in a growing number of domains that affect everyone’s lives, in healthcare, financial services, agriculture, resource management, and beyond.  While data science has huge potential for good, there are also unintended consequences. Data scientists need to take steps  to mitigate as many unintended consequences as they can using Responsible Data Science — a set of policies, procedures, and best practices to ensure algorithmic fairness, transparency, and explainability. 

The Women in Data Science (WiDS) Conference and podcast series has been showcasing  leading women data science experts who are making an impact at the forefront of COVID research. Here are three talks from the conference and three podcasts: