Data-based Decision-making Tool for Proportionality Appraisals in Israeli Targeted Killing Operations (sneak peek)
Sneak peek: Data-based decision making tool for proportionality assessments in Israeli targeted killing operations. (Security Studies Review, 07/06/2020.).
Abstract
Decision makers repeatedly struggle with the dilemmas and perplexities of the principle of proportionality. It is an burdensome task to determine whether or not the attack’s anticipated military advantage is proportional or disproportional to the expected civilian harm (a.k.a. collateral damage), particularly during the often-inimical circumstances under which these decisions must be made. That is also the case in targeted killing operations, which afford relatively comfortable conditions. I have decided to confront this challenging problem because although it is old and known, it was without adequate remedy. I offer a data-based tool for decision makers to evaluate proportionality with. This tool resolves the core complexities in proportionality evaluation for Israeli targeted killings. In order to do that I have created a database with four attack types covering five years. The database maintains each attack in disaggregated form, and each such record contains several variables. The tool retrieves the most relevant direct military advantage that decision makers can expect to achieve by performing the operation. Minor instructions transform the regular assessment of expected collateral damage to the desired form. This platform sets the military advantage and the collateral damage in equivalent terms and in numeric form, and it thus frames an effective comparison. The tool’s flexibility increases functionality and maintains maneuverability for decision makers. It is intended to provide decision makers with a great point of departure to evaluate proportionality based on accumulated data and knowledge (on top of timely intelligence). Modestly put, it solves the majority of their dilemma.
*Originally published: the Security Studies Review, by Shahaf Rabi, 07/06/2020.
Background
What’s Proportionality?
The principle of proportionality is one of the four core principles of the Laws of Armed Conflict, and it encapsulates the other three core principles in it. The principle, codified in the Geneva Conventions, prohibits to perform “an attack which may be expected to cause [civilian harm] which would be excessive in relation to the concrete and direct military advantage anticipated.” Therefore, decision makers need to assess what is the expected civilian harm (also known as collateral damage) and what is the anticipated direct military advantage (interchangeably called military necessity). The comparison of the two and the decision to follow is the proportionality evaluation.
Why This Problem?
The evaluation of proportionality is an onerous task, especially under operational constraints. There is no better person to testify about this hardship than Yuval Diskin, the Israeli Security Agency’s Deputy Director in 2000-2003 and Director in 2005-2011. He is probably the person who was involved in these precise decisions for targeted killing operations more than anyone else in Israel.
(Video below, The GateKeepers, in Hebrew, watch 1:25-3:20)
It is undoubtedly a problem when someone as highly experienced as Diskin battles with proportionality evaluation because if that is the case for him then what is of less experienced decision makers? Also, it is not as if bright minds did not attempt to solve this issue or create tools for decision makers. See for example: Guiora, Byman.
So What’s the Crux of the Problem?
In short, there are two main issues which complicate the evaluation of proportionality, especially for people who care about civilian lives:
(1) It is unclear how broad or narrow should the calculus of military advantage and collateral damage be. As such, the considerations are fluid and holistic since it is ambiguous what to include or exclude in each of them. See for example: Wittes, Blank, Schwartz, Cohen & Shany.
(2) The assessments are subjective – influenced by biases, heuristics, individual’s personality, culture, norms and values. Distinct people assign different weigh to the various elements which compose each of the competing interests (mil. adv. and coll. damage). For example, see: Whittemore, Cohen & Shany.
How I Resolved the Crux of the Problem
This issue bugged me long after I’ve been exposed to Diskin’s testimony. My light bulb moment came after I’ve read Ganor’s book chapter about the proportionality dilemma. He proposed a novel concept: quantified evaluation based on an objective calculation. However, I differed with most of the propositions, even for the more calibrated targeted killings one. It was simply not objective due to the assigned values into variables; the variables’ mathematical operations (e.g. X^2); and the overall calculations. Still, I realized the potential of numerical use in order to overcome the issue of subjectivity. I therefore returned to peruse the law with a numeric perspective in mind.
I sought out the agreed upon fundamentals regarding the above-mentioned first issue of holistic calculations of military advantage and civilians harm. The solid common ground concerns the basics of how states codified the treaty-law and the conservative interpretations of the text. The principle explicitly notes “concrete and direct military advantage anticipated”. That is, the reasonably foreseeable direct result of the attack. It is similarly agreed with regards to collateral damage that the top priority – which is also most tangible – is the physical harm to civilians (fatalities and physical wounds).
Hence, consider the simplified proportionality evaluation below in preparation for numerical evaluation:
Proportional (attack may proceed):
direct military necessity anticipated >= expected civilian harm.
* though note the expected civilian harm may be greater than the anticipated direct military advantage for as long as it is not “excessive”. Then again, this would have us circle back to issues of subjectivity.
Importantly, the operations conducted as a part of Israel’s targeted killing policy deal with the ones which serve the purpose of thwarting specific Palestinian attacks that the security services obtained information on before the attacks materialized.
I figured that as the purpose is to prevent attacks, then this is the perfect fit for direct military necessity anticipated. There is a rich historical record of Palestinian attacks and their respective results in terms of fatalities and physical injuries. So I created a dataset with the details of individual attacks (especially the attack types and casualties). Therefore, I solved the first issue of holistic calculations since both, the military necessity and civilian harm, are expressed in terms of fatalities and physically wounded people.
Moreover, this actually also solves the subjectivity issue. The reason for this is that the database records physical casualties for the military necessity. These are facts, objective numbers. Similarly, the expected civilian harm is also based on assessments of the number of fatalities and injuries. Consequently, the anticipated direct military necessity in terms of foiling an attack by performing a targeted killing is in the form of objective numbers, and so is the expected collateral damage.
The platform therefore frames an effective comparison as it sets the military advantage and the civilian harm in equivalent terms and in numeric form. The most basic of intelligence information about the impending attack, the modus operandi, already enables this data-based tool to retrieve the most relevant* direct military necessity that decision makers can expect to obtain if the targeted killing is carried out in order to thwart the threat. With this as anchorage point, the only possible adjustment needed to compare the military necessity with the civilian harm is to ensure the regular assessment of expected collateral damage relates to physical casualties. At minimum, this quick and simple solution solves decision makers’ most difficult part in proportionality appraisal. However, it neither replaces their discretion nor determine for them if the proposed attack is proportional or not.
*Relevant as in the tool retrieves values based on their percentile location. It avoids the use of the average which is susceptible to extreme cases. Further adjustments depend on available intelligence information (timely and past research – as exemplified later on).
INSIGHTS (sneak peek)
Important acronyms:
for Modus Operandi variable:
1.1. SMS (Suicidal Mass-Shooter)
1.2. SB (Suicide Bomber)
1.3. VBED (Vehicle-Borne Explosive Device)
1.4. SB VBED (Suicide Bomber via Vehicle-Borne Explosive Device)for De-Facto Target variable:
2.1. PT (Public Transportation)
2.2. SF (Security Forces)
2.3. O (Other)
Overview of the Data
DATA ANALYSIS INSIGHTS – For Smarter Usage
The data analysis provided opportunities to identify KPIs (key performance indicators) since the established database contains a number of cataloged variables, and some of them proved relatively insignificant. This sneak peek focuses on the two most important indicators: the modus operandi; and the de-facto target.
How many times each modus operandi targeted Other, Public Transportation & Security Forces
How many casualties (fatalities/injuries) for each modus operandi, sorted by target (Other, Public Transportation, Security Forces)
It is useful to gain insights from data analysis for smarter military necessity assessment. For instance, there are attack types such as the VBED with 46 incidents in total, a fairly small number. This might become a problem if intelligence points to an organization like Hamas that is about to stage a VBED attack. If filtered by Hamas, 3 incidents are left in total. Yet after in-depth analysis, there is no evident difference between attacks’ lethality when comparing organizations. It means the assessment should not refine the military necessity anticipated by organization in this case. However, the fact Hamas facilitates the attack is important because Hamas overall inclines to target public transportation and other – a KPI.
DATA ANALYTICS INSIGHTS – Knowledge/Data-based Direct Military Necessity Anticipation
The decision makers need to have at their disposal a platform that is informative and easy to comprehend. The intelligence services need to make available the concrete intelligence information for the impending attack as well as supplementary intelligence analysis reports in order to determine the layers upon which the assessment of the anticipated direct military necessity is to be based on. The KPIs constitute the backbone of the assessment. Further intelligence analysis can help indicate other patterns, preferences, et cetera which may be relevant to the assessment (e.g. previous example of Hamas’ target choice tendency). On top of this, the concrete intelligence information need be put, including possibly, recommendations in advance to opt for a certain percentile range. For instance, to opt for 50% percentile range and strongly recommend refraining from increases to a certain degree in cases of modus operandi with thousands or more of cases recorded in the database, as opposed to modus operandi of much smaller recorded cases.
An approachable user-interface greatly matters. The platform itself clearly visualizes to the decision makers the percentile range as well as indicate the spread of the values since they can see the median and the values at each edge of the percentile range. These help widen their perspective, as exemplified below (reflects the overall direct military necessity anticipated in case of suicide bomber attacks).
Direct military necessity anticipated for suicide bombers
Finally, the decision maker(s) need to know the assessment with regards to the expected civilian harm, which might also be given as a range depending on the circumstances at hand.
Proportionality Evaluation – Uncomfortable & Unintuitive Cases in Point:
Let us take some inspiration from Yuval Diskin’s testimony about proportionality evaluation. You are the commander in charge in the three given scenarios. Your final decision, should you make one, matters less than your ability to make rapid, informed, and sagacious proportionality evaluations.
(1) You finally know the cell phone number that the PIJ’s suicide bomber carries with him. This enables you to pinpoint his location, and you find out the bomber is traveling in a taxi. You have no clue how many people are in it, although you assess it is a civilian taxi driver at minimum and up to additional 3 other civilians. You know the bomber was told to explode at one of the city’s most popular streets with many bars and restaurants, and also, not to waste time. The taxi travels through a quiet street, seems without people. There is no time to pass on the information to security personnel on the ground before the bomber reaches his destination. The line is open with the IAF’s command and control operations room. They see what you see. The drone is ready to fire a missile. Whoever is in the taxi is expected to be killed. Is it proportional to strike? (which does not necessarily mean you’d order the airstrike. You may choose to let the bomber go ahead, and probably explode while you cross your fingers for a malfunction of any sort of the explosive belt).
Direct military necessity anticipated for a suicide bomber targeting “Other”
(2) IAF drone tracks a suicide bomber in the West Bank. He travels in a Palestinian taxi with the driver and another unknown Palestinian. As the commander, you hope to wait for a moment of opportunity to strike without any uninvolved people around. However, you see the taxi is about to arrive to a flying-checkpoint manned by five IDF soldiers. The soldiers are unaware of the danger and cannot be warned in time. Do you conduct an airstrike at the Palestinian taxi or see how things play out at the checkpoint?
Direct military necessity anticipated for a suicide bomber targeting “Security Forces”
(3) You located the suicide bomber at a junction with two unknown people, most likely Israeli civilians. They ordered one of Dan’s Bubble minibuses (i.e. 10 seats max.) and it is about to arrive to them in no more than two-three minutes. This is a Hamas suicide bomber, and thus you assess she is likely to explode in it. While the other personnel under your command do their best to find out with Dan how many passengers are currently in the minibus, and to contact the driver, you need to consider whether you should act in case the efforts won’t bear fruits in time.
Direct military necessity anticipated for a suicide bomber targeting “Public Transportation”
SOME TECHNICAL NOTES
(1) I knew from previous researches that there was no adequately comprehensive, reliable, and publicly available dataset of Palestinian attacks. It had to be created. I thus designed and used the methodology and coding rules document for the Palestinian & Co. Political Violence database (hereinafter, database).
(2) The reports of the ISA (aggregated summaries) proved useful for the purposes of choosing which kind of attack types to prioritize and to collect due to time and other constraints.
(3) I created the database. Subsequently, I imported the 357 relevant attack cases to a new Excel file, and in Excel’s Manage Data Model/Power Pivot, I further prepared the data for analysis. For instance, I removed redundant cataloged variable-columns for the purposes of this analysis.
(4) I conducted analysis in order to identify KPIs and gain additional insights. This required to add some DAX at the calculations area, such as the retrieving the fatalities and injuries values in the right percentiles. Moreover, I used the Power Pivot functions to re-arrange the data and to create new tables for some additional customized investigation of the data, to visualize the data, and so on, in order to gain further insights.