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In an effort to provide early warning capabilities, the Department of Defense’s Integrated Crisis Early Warning System (ICEWS) and IARPA’s Open Source Indicators (OSI) programs want to leverage novel statistical and machine learning techniques using publicly available data sources to forecast societal such as civil unrest and disease outbreaks with a high degree of accuracy.
Surprise events such as the fall of the Berlin Wall, Iraq’s invasion of Kuwait, the civil unrest that gave rise to the Arab Spring, and Russian incursions into Ukraine, forced rapid responses in the absence of data related to the underlying causes of these events.
In an effort to strengthen global crisis response capabilities, The IARPA Mercury Challenge seeks innovative solutions using machine learning and artificial intelligence methods to automatically predict the occurrence of critical events involving military action, non-violent civil unrest, and infectious diseases in Egypt, Saudi Arabia, Iraq, Syria, Qatar, Lebanon, Jordan, and Bahrain.
Participants are encouraged to develop and test innovative forecasting methods that ingest and process publicly available data sources to predict Military Activity, Non-violent Civil Unrest, and Infectious Disease in specific places of interest. Participant forecasts will be scored across a three-month rolling window. Every month, IARPA will score those participants who have sent forecasts for three consecutive months. Scoring will be based on four metrics including forecast lead time, location accuracy, date accuracy, and facet actor/event-type matching. This challenge is scheduled to run from July 2018 until early 2019 when winners are announced. Technologists, data scientists, and machine learning engineers who are skilled at breaking down complex data are encouraged to join. Individuals ranging from private industry and academia are all eligible to participate and win prizes. The Mercury Challenge Team believes success in this challenge can prove to be a strong addition to any data science practitioner’s portfolio.
The Mercury Challenge seeks innovative solutions and methods for the automated generation of event forecasts in the Middle East and North Africa.
The three specific event classes of interest are:
- Military Activity (MA) in Egypt, Saudi Arabia, Iraq, Syria, Qatar, Lebanon, Jordan, and Bahrain:
- Conflict – Incident where police, military, or other state/government security forces take action in some way; and
- Force posture – A newsworthy action of police, military, or other state/government security forces that does not involve the use of deadly force.
- Non-violent Civil Unrest (CU) in Egypt and Jordan, such as demonstrations, marches and protests:
- Daily count of non-violent civil unrest events in Egypt
- Weekly count of non-violent civil unrest events in Jordan
- Weekly count of non-violent civil unrest events in a 75km radius of Tahrir Square, Egypt
- Monthly count of non-violent civil unrest events in the Jordanian provinces of Amman, Madaba, and Irbid.
- Infectious disease in Saudi Arabia: Weekly MERS count.
WHO WE ARE
The Intelligence Advanced Research Projects Activity (IARPA), within the Office of the Director of National Intelligence (ODNI), focuses on high-risk, high-payoff research programs to tackle difficult challenges of the agencies and disciplines in the intelligence community. IARPA’s challenges invite experts from the broader research community to participate in IARPA research in a convenient, efficient, and non-contractual way.
WHAT WE’RE DOING
IARPA is looking for innovative machine learning techniques that would improve the accuracy and timeliness of global forecasts. IARPA hosts these challenges to identify ways that individuals, academia, and others with a passion for forecasting can showcase their skills easily.
Opportunity is About:
Candidates should be from:
Description of Ideal Candidate:
WHO SHOULD PARTICIPATE
Technologists, data scientists, and machine learning engineers who are skilled at breaking down complex data are encouraged to join. Individuals ranging from private industry and academia are all eligible to participate and win prizes. The Mercury Challenge Team believes success in this challenge can prove to be a strong addition to any data science practitioner’s portfolio.
Certain individuals and groups with existing agreements with IARPA may not be eligible for cash prizes but may be able to compete for standing on the leaderboard and other non-monetary incentives. Additional eligibility rules will be available closer to launch.
RULES & ELIGIBILITY
To be eligible to win a prize under this competition, an individual or entity:
- Must be (1) an individual or team each of whom are 18 years of age and over, or (2) an entity incorporated; and
- May not be a federal entity or federal employee acting within the scope of their employment. An individual or entity shall not be deemed ineligible because the individual or entity used federal facilities or consulted with federal employees during a competition if the facilities and employees are made available to all individuals and entities participating in the competition on an equitable basis.
Federal grantees may not use federal funds to develop challenge solutions unless consistent with the purpose of their grant award. Federal contractors may not use federal funds from a contract to develop challenge applications or to fund efforts in support of a challenge submission.
Deadline: April 30, 2019
Cost/funding for participants:
WHY SHOULD YOU PARTICIPATE
This challenge gives you a chance to join a community of leading experts to advance your research, contribute to global security and humanitarian activities, and compete for cash prizes. This is your chance to test your forecasting skills and prove yourself against the state-of-the-art, and to demonstrate your superiority over political pundits.
By participating, you may:
- Network with collaborators and experts to advance your research
- Gain recognition for your work and your methods
- Test your methods and monitor how you stack up amongst competitors
- Win prizes from a total prize purse of $100,000