Citizen Science and Artificial Intelligence Technologies: Collaborating for an Innovative and Unbiased Future - Free webinar, 9 October
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“Citizen Science and Artificial Intelligence Technologies” is an online webinar that aims to bring together the power of citizen participation and the potential of emerging technologies.
In this era of rapid technological advancements, citizen science provides a unique opportunity to engage individuals from diverse backgrounds in scientific research and innovation. By involving citizens in data collection, analysis, and problem-solving, we can tap into the collective intelligence of the crowd, accelerating scientific discovery and fostering a deeper understanding of our world.
Interdisciplinarity in these areas unlocks new possibilities for addressing complex challenges in areas like the labour market, environmental conservation, public health, and urban planning. This collaboration enables harnessing the power of technology to amplify the impact of citizen-driven initiatives, facilitating real-time data collection and data sharing. At the same time, practices and methodologies inspired by citizen-science can be used to consult and engage users and stakeholders in AI research, and make sure computer scientists get input and feedback that contribute to increasing inclusiveness and trustworthiness of the systems they design.
This webinar is a combined effort of the TIME4CS and BIAS projects, bringing together the Citizen Science Helix and the Trustworthy AI Helix communities.
To register visit: https://bit.ly/3YLGURd
Should you have any questions about this event please don't hesitate to contact us at [email protected]
Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the granting authority. Neither the European Union nor the granting authority can be held responsible for them. This project has received funding from the European Union’s Horizon 2020 or Horizon Europe research and innovation programme under grant agreement No 101006201.
