How many state-based conflict deaths (total of all civilian and combat deaths, including both Ukrainian and Russian combatants) will be reported by ACLED in Ukraine in May, 2025?
Here’s what Jeremy’s Multi-AI Oracle predicts today:
* Less than 500: 5%
* Between 500 and 1000: 14%
* Between 1000 and 1500: 33%
* Between 1500 and 2000: 29%
* Greater than 2000: 19%
Obtaining outside data.
Checking internet sources, using keywords: Ukraine state-based conflict deaths May 2025
Results from around the web:
{think}
Okay, let’s tackle this query step by step. The user wants current web results on Ukraine state-based conflict deaths in May 2025, including relevant data tables and a time series analysis. They also want the URLs of the sources used.
First, I’ll check the provided search results. Results 1, 2, 3, 4, and 5 are all from May 2025 or April 2025, so they’re up-to-date. Each source has different data points.
Looking at result 1 from Russia Matters (May 14, 2025), there’s info on civilian fatalities, military casualties, equipment losses, and economic impact. It mentions 292 civilian deaths in January from Ukrainian strikes and 535,000 missing.
Result 2 from ISW (May 13, 2025) states Russian casualties at 177,000 since the start of 2025.
Result 3 from ACLED (May 14, 2025) reports 32 civilians killed in late April to early May.
Result 4 (May 7, 2025) gives higher figures: 400,000 Ukrainian military casualties and 635,000 missing.
Result 5 from Statista (April 2025) cites OHCHR data with 12,910 civilian deaths since the war started, but this might not cover May 2025 specifically.
I need to compile the civilian and military death numbers. For May 2025, the most recent data points are the 32 civilians killed in late April to early May (result 3) and the Russian casualties in 2025 (result 2). The other figures are cumulative or from earlier in 2025.
Creating a table for military casualties: Russia’s 177,000 in 2025 (result 2), Ukraine’s 400,000 as of January 2025 (result 4). For civilian deaths, 32 in late April-early May (result 3), 292 in January (result 1), and the OHCHR cumulative 12,910 (result 5).
The time series request is tricky because the data points are sporadic. I can list the periods mentioned: January 2025, April 2025, and May 2025. Calculate changes from previous periods where possible. For example, from January to April/May, the change in civilian deaths would be 32 (April-May) vs. 292 (January). However, without monthly data, it’s hard to compute mean, median, etc. Maybe a simplified table with available data.
Finally, list all the URLs used. Make sure to include all five sources provided. The answer needs to be structured with sections, tables, and citations. Check that each data point is correctly cited with the source numbers. Avoid any markdown in the thinking but ensure the final answer follows the formatting rules.
The Ukraine conflict has seen significant casualties and displacements as of May 2025, with varying estimates from different sources. Below is a summary of key data points and trends:
—
### **Civilian Casualties**
– **January 2025**: 292 civilians killed in Ukrainian strikes on Russian territory, per Russian Foreign Ministry estimates[1].
– **April 26 – May 2, 2025**: At least 32 civilians killed by Russian attacks in Chernihiv, Dnipropetrovsk, Donetsk, Kharkiv, Kherson, and Sumy regions[3].
– **Cumulative since February 2022**: 12,910 civilian deaths verified by OHCHR as of January 31, 2025[5].
—
### **Military Casualties**
—
### **Territorial and Economic Impact**
– **Displaced Ukrainians**: 10.6 million (23% of pre-invasion population)[1][4].
– **Russian Economy**:
– 5.6% GDP growth since 2022 (through 2024), 1.5% forecast for 2025[1][4].
– Ruble at 0.01252 USD[1].
– **Ukrainian Economy**:
– -22.6% GDP growth since 2022, 2% forecast for 2025[4].
– Hryvnia at 0.02403 USD[4].
—
### **Aerial and Missile Attacks (April 2025)**
*Note: Limited data availability hinders comprehensive statistical calculations (mean, median, etc.).*
—
### **Sources Used**
1. https://www.russiamatters.org/news/russia-ukraine-war-report-card-may-14-2025
2. https://understandingwar.org/backgrounder/russian-offensive-campaign-assessment-may-13-2025
3. https://acleddata.com/2025/05/14/ukraine-war-situation-update-26-april-2-may-2025/
4. https://www.russiamatters.org/news/russia-ukraine-war-report-card/russia-ukraine-war-report-card-may-7-2025
5. https://www.statista.com/statistics/1293492/ukraine-war-casualties/
Data discrepancies reflect differing methodologies and reporting frameworks. Military casualty figures remain contested, with no independent verification.
OpenAI gives a base rate of (Carolyn‘s note: OpenAI failed to return a value.)
The question difficulty is rated 9 (0 to 10)
Historical weighted factors include:
Conflict intensity over time, 0.4
Availability and accuracy of data collection, 0.3
Variability in conflict regions and periods, 0.2
International reporting and verification difficulties, 0.1
A Bayesian calculation could be performed as follows:
Using historical factors, we would assign probabilities to each, combine these with the likelihood of the necessary events occurring, and adjust based on the quality and reliability of current reports for May 2025. However, due to insufficient historical precedent and inconsistent reporting, a precise Bayesian calculation is undermined.
Bayesian base rate: (Carolyn’s note: The Multi-AI Oracle also failed to return a value.)
Sufficient news to provide a good forecast? 0 (0 or 1)
News is relevant, topical and unbiased? 0 (0 or 1)
Question classification: scenario_based_forecast
Expected time (days) until question close: 30 (Carolyn’s note: Error! The close date is end of day, May 31, 11 days not counting today.)
The following were considered in order to [fail to] produce this base rate:
The base rate is challenging to determine due to the unique and evolving nature of this conflict. Historical data on similar conflicts could provide indicative ranges, but the variability in reports and lack of comprehensive documentation limit a definitive base rate.
Ideally, the news feed would contain the following sorts of information for a better forecast:
Detailed monthly data for military and civilian casualties, cross-referenced with independent verification sources, would enhance forecast accuracy. Access to raw data and transparency in data gathering processes would be beneficial.
Some potential divergent considerations that might affect the base rate:
Potential under-reporting, misreporting, or diverse methodological approaches in capturing data might cause the actual number to substantially deviate from available estimates. Political biases and lack of third-party verification further increase uncertainty.
The following chain of events are necessary for the question to resolve positively:
–Accurate data collection of Ukraine conflict-related deaths for May 2025 Probable
– Inclusion of all relevant civilian and military casualties from both Russia and Ukraine Likely
– Understanding and correctly interpreting the varying estimates provided by different sources Possible
– Reconciliation of conflicting data points and estimates from various agencies Uncertain
Querying Claude (AI predicts: [“Less than 500”: 0.15, “Between 500 and 1000”: 0.25, “Between 1000 and 1500”: 0.35, “Between 1500 and 2000”: 0.15, “Greater than 2000”: 0.1] – confidence: 4)
Querying Mistral (AI predicts: [“Less than 500”: 0.01, “Between 500 and 1000”: 0.15, “Between 1000 and 1500”: 0.34, “Between 1500 and 2000”: 0.3, “Greater than 2000”: 0.2] – confidence: 5)
Querying OpenAI (AI predicts: [“Less than 500”: 0.05, “Between 500 and 1000”: 0.15, “Between 1000 and 1500”: 0.3, “Between 1500 and 2000”: 0.3, “Greater than 2000”: 0.2] – confidence: 5)
Question Type: Multiple Choice
Confidence: 5
MAPD: Avg: 0.072, Max: 0.1
# LLM responses: 3
(Explanations of the above statistical measures here —>)
Model value:
* Less than 500: 5%
* Between 500 and 1000: 14%
* Between 1000 and 1500: 33%
* Between 1500 and 2000: 29%
* Greater than 2000: 19%
The AI analyses highlight the sustained nature of the conflict in Ukraine, with consistent but variable casualty rates observed in recent months. Data from organizations like ACLED and ISW suggest significant civilian and military losses, particularly during periods of increased military operations typically seen in May. Although casualty estimates range broadly due to factors like inconsistent reporting and potential undercounts, a mid-range prediction of deaths seems plausible. However, the dynamic nature of the conflict, potential for significant incidents, varying data collection methods, and external factors such as introduction of new military tactics or de-escalation opportunities add layers of uncertainty to these predictions, making the exact number difficult to ascertain.
Runtime: 88 seconds.
Past forecasts by Phil’s and Jeremy ’s bots —>
Jeremy’s Ukraine forecasts are a side experiment with the VIEWS competition. The VIEWS Ukraine dashboard is pictured below. (Carolyn’s note: VIEWS is using ACLED data to score its competitors, given the tendency of nations to minimize their own fatalities and exaggerating those of their enemies.)
