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The War in Ukraine: Challenges in Documenting War Crimes and Russian False Flags

Monday, June 27 @6:00 PM

Overview

We have a great three-part meetup to kick start Data+AI Summit 2022!



• The War in Ukraine: Challenges in Documenting War Crimes and Russian False Flags

• MLflow Panel



AI Squared
TBD



The War in Ukraine: Challenges in Documenting War Crimes and Russian False Flags
Communications about the situation in Ukraine, both within the country and beyond in the wider world, create a daily flood of messaging, witnessing, and political and diplomatic maneuvering. The availability of data has created a problem: because so much is happening in open venues online, there are numerous emergent challenges in the collection and documentation of this deluge of data. Time is of the essence here, as the data may disappear as quickly as it is posted online, as the ephemerality of social media and messaging data is profound.



Presently, there is no standard way to collect and preserve the vast information regarding Ukraine that circulates daily, and will continue to do so as the conflict continues. Absent greater coordination and communication among the growing community of public interest investigators there is a risk that critical evidence will be lost or inaccessible to the very prosecutors, tribunals and fact-finding bodies that will need them the most. Moreover, without a set of agreed on protocols, standards and/or guidelines for the collection, collation, archiving and dissemination the available data it will be impossible to capture, preserve, and study the informational and evidentiary contrails of the evolving humanitarian rights crisis in Ukraine. At best there is a risk of duplicating efforts. At worst there is an equal concern that data that is collected may be unusable in any legal proceeding.



This only scratches the surface of challenges that face the journalists, engineers, and researchers who are trying to help. A cloud of disinformation in the form of conspiracy theories and false flag stories envelop and confounds any data collection and analysis, making the establishment of disinformation just as important as collecting and validating reliable information.



MLflow and MLOps Ask-Me-Anything Panel
Join MLflow contributors and committers …

Type

  • Meetup

Format

  • In-Person

Track

  • Meetup

Room

  • Moscone South | Level 3 | 301-302

Duration

  • 180 min

Session Speakers

Jim Hibbard

Senior Developer Advocate

Databricks

Shawn Walker

Assistant Professor of Data & Society

Arizona State University

Michael Simeone

Associate Research Professor

Arizona State University

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