BS Summary: This article contains 21 faulty reasoning types, including Appeal to Authority, Indoctrination, and Framing Effect, with Biased Writer Voice as the most egregious example at 46.6% saturation with 95 hits. Analysis detected 767 faulty-reasoning hits from 204 analyzed words, generating a BS Score of 77.3% and a BS Rank of 85% (2,983 of 18,848 articles). This article is worse (more manipulative) than 84.20% of the article peer group.

Over the past two decades, U.S. security assistance has dramatically increased, with mixed results. 
The United States’ failure to build effective partner security forces in places like Afghanistan and Mali has raised questions about the efficacy of U.S. security assistance approaches. 
Yet, when done right, security assistance to key partners can allow the United States to advance central national security goals, as recently seen in Ukraine. 
Within a rapidly changing strategic context, what is the future of security assistance? 
How can the United States reform its security assistance approaches to increase its return on investment, especially in theaters described as lower priority by the Trump administration like Africa? 
On July 20, join the Strobe Talbott Center for Security, Strategy, and Technology at Brookings for a discussion on this topic with Rep. 
Sara Jacobs (D-Calif.), ranking member of the House Foreign Affairs Subcommittee on Africa. 
Brookings experts Dafna H. 
Rand, the former director of foreign assistance at the Department of State, and Alexander Noyes, the coauthor of “War at Arm’s Length: How America Can Build Effective Partners Through Military Assistance,” will moderate this event. 
Viewers can submit questions via e-mail to <a href="/cdn-cgi/l/email-protection" class="__cf_email__" data-cfemail="1d786b7873696e5d7f6f72727674737a6e33787968">[email&#160;protected]</a> or via Twitter at <strong>#SecurityAssistanceReform</strong>. 
Confirmation Bias
14.2%
Anchoring Bias
0%
Availability Heuristic
13.2%
Representativeness Heuristic
0%
Hindsight Bias
0%
Overconfidence Bias
0%
Framing Effect
23%
Loss Aversion
0%
Status Quo Bias
14.2%
Sunk Cost Effect
0%
Optimism Bias
12.3%
Pessimism Bias
0%
Negativity Bias
20.1%
Self-Serving Bias
0%
Fundamental Attribution Error
13.2%
Actor-Observer Bias
0%
In-Group Bias
0%
Out-Group Homogeneity Bias
0%
Halo Effect
12.3%
Horn Effect
0%
Dunning-Kruger Effect
0%
Recency Bias
19.1%
Primacy Effect
17.2%
Blind-Spot Bias
0%
Ad Hominem
0%
Straw Man
0%
Appeal to Authority
23.5%
False Dilemma
14.2%
Slippery Slope
0%
Circular Reasoning
0%
Hasty Generalization
13.2%
Red Herring
0%
Bandwagon
0%
Appeal to Emotion
0%
Begging the Question
0%
Post Hoc (False Cause)
0%
Tu Quoque
0%
Burden of Proof
0%
Appeal to Nature
0%
Composition/Division
0%
Anecdotal
12.3%
No True Scotsman
12.3%
Ambiguity (Equivocation)
21.1%
Gambler’s Fallacy
0%
Middle Ground
0%
Personal Incredulity
0%
Special Pleading
0%
Genetic Fallacy
0%
Unattributed Quote
17.2%
Quote-first Misdirection
0%
Biased Writer Voice
46.6%
Indoctrination
23.5%
Politically Left Leaning Bias
0%
Politically Right Leaning Bias
14.2%
Attempt to Sell a Product or Service
19.1%

204 words analyzed.

Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.