How many state-based conflict deaths in Syria will be reported by ACLED for the month of May 2025?
Here’s what Jeremy Lichtman’s Multi-AI Oracle predicts today:
* Less than 100: 1%
* Between 100 and 250: 11%
* Between 250 and 500: 29%
* Between 500 and 1000: 35%
* Greater than 1000: 24%
Obtaining outside data.
Checking internet sources, using keywords: ACLED conflict deaths Syria May 2025
Results from around the web:
Okay, let’s tackle this query. The user is asking for current web results related to ACLED conflict deaths in Syria for May 2025, along with tables of data and a time series analysis. They also want the sources listed at the end.
First, I need to go through the provided search results. Looking at the sources:
– Source [1] from ACLED mentions 803 individuals killed between March 6-10, 2025, as reported by the Syrian Network for Human Rights (SNHR). That’s a key figure, but the date is March, not May. Wait, the URL says May 2025, but the content mentions March. Maybe it’s a typo or the report covers events up to May but includes earlier data. Need to check the date of the source: 2025-05-08. So the report is from May 8, 2025, discussing events up to that point. The 803 deaths in March would be part of the May overview.
– Source [2] from SNHR talks about American citizens killed in Syria, mostly by the Assad regime and ISIS. It’s from May 12, 2025. Not directly about conflict deaths in May, but relevant as it shows ongoing violence involving the regime.
– Source [3] from ReliefWeb, dated May 9, 2025, citing ACLED data, reports a 138% increase in fatalities from US strikes in April, with 362 deaths, including 150 civilians. This is crucial as April is just before May, and the increase is significant. However, the user asked for May data. But if this report is from May, it might be summarizing April’s data as part of the May overview. The user might want to include this as the most recent available data.
– Source [4] is the ACLED homepage, which is just general info about the organization. Not directly useful unless there’s specific data, but the user is looking for ACLED’s data, so maybe citing this as the main source.
– Source [5] is Wikipedia on the Western Syria clashes from March 2025. It mentions 1,659 civilians killed according to SOHR and 823 per SNHR. Again, March data, but the report is from May (the URL is May 2025). So this is part of the ongoing conflict covered in May reports.
OpenAI gives a base rate of proportion of similar past periods with fatalities greater than 1000
The question difficulty is rated 6 (0 to 10)
Historical weighted factors include:
Historical average monthly fatalities, 0.5
Current conflict intensity, 0.3
Recent increase in fatality trends, 0.2
A Bayesian calculation could be performed as follows:
B_prior = 0.7; Likelihood of evidence given event (high deaths): 0.8; Posterior Probability = B_prior * Likelihood / normalizing constant = 0.7 * 0.8 / 0.8 = 0.7
Bayesian base rate: 0.7
Sufficient news to provide a good forecast? 1 (0 or 1)
News is relevant, topical and unbiased? 1 (0 or 1)
Question classification: reference_class
Expected time (days) until question close: 31 (Carolyn’s note: Error as 16 days remain in May.)
The following were considered in order to produce this base rate:
The base rate is determined by considering previous months where conflict deaths exceeded 1000. The information about the ongoing situation and previous trends informs this rate.
Ideally, the news feed would contain the following sorts of information for a better forecast:
Additional details on the ground situation in Syria, including movements and strategies of involved factions, and access to finer granularity ACLED or relevant conflict data would enhance forecast quality.
Some potential divergent considerations that might affect the base rate:
Resolution could differ if there is an unexpected ceasefire or sudden decrease in conflict intensity.
The following chain of events are necessary for the question to resolve positively: (Carolyn’s note: By “positively”, this bot means for its forecast of increasing fatalities to come true.)
– Continued involvement and escalation of conflict by various factions including the Assad regime and ISIS Almost Certain
– Reports from credible sources (ACLED, SNHR) indicating high fatalities Likely
– Ongoing airstrikes and armed confrontations throughout the region Probable
Querying Claude (AI predicts: [“Less than 100”: 0.05, “Between 100 and 250”: 0.15, “Between 250 and 500”: 0.35, “Between 500 and 1000”: 0.3, “Greater than 1000”: 0.15] – confidence: 6)
Querying Mistral (AI predicts: [“Less than 100”: 0.01, “Between 100 and 250”: 0.09, “Between 250 and 500”: 0.25, “Between 500 and 1000”: 0.45, “Greater than 1000”: 0.2] – confidence: 7)
Querying OpenAI (AI predicts: [“Less than 100”: 0.01, “Between 100 and 250”: 0.05, “Between 250 and 500”: 0.1, “Between 500 and 1000”: 0.24, “Greater than 1000”: 0.6] – confidence: 7)
Question Type: Multiple Choice
Confidence: 7
MAPD: Avg: 0.14, Max: 0.3
# LLM responses: 3
(Explanations of the above statistical measures here —>)
Model value:
* Less than 100: 1%
* Between 100 and 250: 11%
* Between 250 and 500: 29%
* Between 500 and 1000: 35%
* Greater than 1000: 24%
The recent analyses of conflict data in Syria suggest an escalation, marked by a 138% increase in reported deaths in April 2025 compared to historical patterns. Major contributors to this trend include the active involvement of the Assad regime, ISIS, and U.S. military operations. Historical data typically shows casualty figures ranging between 250-1000 per month, indicating that the recent spike could be part of an ongoing escalation phase. However, there is a possibility that fatalities may stabilize in the coming months. The predictions of continued high casualties are supported by ongoing airstrikes and armed confrontations, yet several factors could lead to inaccuracies such as unexpected ceasefires, changes in military strategies, and potential reporting discrepancies. Additionally, the inherent unpredictability of conflict situations and possible alterations in data collection methodologies further contribute to uncertainty in forecasting future casualty figures.
Runtime: 68 seconds.
Past forecasts by Phil’s and Jeremy ’s bots —>
Below, a forecast of state-based conflict fatalities for Syria in the VIEWS machine forecasting competition, which is an aggregate of the forecasts of twenty competitors. Our botmasters, Phil Godzin and Jeremy Lichtman, are conducting a side experiment with VIEWS.
