Search

While many may think, that we have come far in matters of anti-discrimination and diversity, the sad truth is: we have a long way to go. We see this in various incidents:

  • Training algorithms with existing data can lead to a consolidation of existing structures, as an algorithm to aid HR at Amazon showed.
  • Facebook’s algorithms have been criticized for replicating discriminatory structures, which have been actively exploited.
  • Health care is highly discriminatory, as many studies in the past have not considered different genders or ethnos sufficiently - and this concerns algorithms, which are supposed to support medical staff, as well as the knowledge of the medical staff itself.
  • Lower accuracy for different groups of people of face recognition software is a well known issue, coming from unsufficient training data.

The problems are not always obvious or intended, nonetheless they exist and we want to make them visible.

With the “Proud and Strong in Computing Conference” (PSCC) we want to create a platform to increase the visibility of underrepresented groups in the field of scientific and high-performance computing and discuss measures and opportunities to foster a welcoming athomosphere for everyone in our community. Together we want to create a platform for (multiply) marginalized persons in the HPC-environment for networking, open discussions and presentation of their research. To achieve this, the conference is designed with a multi-disciplinary approach with several contribution tracks and a panel discussion.

Research Track: Proud and Strong through Diversity

If your research is concerned with diversity in research - in computer sciences, cognate disciplines or in general - we would love to hear from you! In this track, especially talks from the fields of

  • social studies,
  • gender studies,
  • economics,
  • ethics,
  • and related,

are welcome.

Track: Best Practices for Employers

In this track, we offer a stage for best practices of employers regarding diversity. This track is strongly related to the panel discussion. Please consider contributing a talk describing:

  • your challenges establishing a diverse workforce,
  • best practices in your institute or company in the employment process,
  • best practices in your institute or company for a welcoming atmosphere.

Research Track: Scientific Computing

We welcome scientific talks from all areas of scientific computing that you like to share in a welcoming environment, including, but not limited to,

  • life sciences,
  • digital humanities,
  • AI,
  • deep and machine learning,
  • numerics,
  • physics and chemistry.

While your presentation should focus on the scientific content, we also welcome some aspects of proud and strong in computing during the talk. Maybe your personal background contributed in a special way to your research? Maybe you made positive or negative experiences?

Track: Personal Experiences

In this track we would like to hear your experiences - bad and good - as a member of an underrepresented group in scientific computing. We think it is necessary for employers to learn from first-hand experiences. And most likely they will not get it from their employees. This track focuses on the exchange of experiences across different companies and intitutes. Please consider contributing a talk in this track presenting:

  • your experiences as a member of an underrespresented group in scientific computing and cognate disciplines,
  • your experiences as a caring relative or as a parent.

How does belonging to an underrepresented group influence your work or research? How does it influence the choice of your job? Have you experienced a very welcoming atmosphere somewhere? What was so special or different there?

Panel Discussion

In the panel discussion we would like to discuss diversity and especially integration culture in the employment process and thereafter. We all know the almost mandatory phrases “we particularly encourage applications from women, disabled and Black candidates”, or “We particularly welcome Black, Asian and Minority Ethnic, disabled, female and trans applicants because these groups are currently under-represented in our workforce.”. Additionally, we see that job offers are directed at “m/f/d” - but is this enough?

What happens afterwards? What kinds of welcoming cultures are established in different institutes or companies? What are your experiences and best practices? We would like to see both sides on the panel: officials being responsible for hiring as well as applicants and employees who are addressed with these phrases.

How comfortable are you with these phrases?