12 U.S. Government (2009) Structured Analytic Techniques
Discussion: Which of the 12 U.S. Government (2009) Structured Analytic Techniques do you think best enable analysts to reduce cognitive and perceptual biases? Pick one diagnostic, one contrarian, and one imaginative thinking technique and describe why you chose those three. In the article, The future of the intelligence analysis task by Hare and Coghill (2016), they describe how technology and artificial intelligence will impact the intel analysis function. Do you think the skills necessary to be an effective intelligence analyst in the future will be fundamentally different than those used by analysts just before 9/11?
Response #1 (Brad): Hello Class and Dr. G,
When looking at the 12 U.S Government Structured Analytic Techniques best reduce cognitive and perceptual biases, three categories stand out. These categories are diagnostic, contrarian, and imaginative thinking techniques.
The diagnostic technique is the analysis of competing hypothesis (ACH). This is effective in mitigating biases by systematically comparing multiple hypothesis. It forces the analyst to consider alternatives that may not align with their initial assumptions. This reduces the confirmation bias that often skews judgement.
The next is the contrarian technique. this is also known as Red Team Analysis. This technique challenges existing plans and viewpoints by assuming an adversarial role. Red Team Analysis is crucial to exposing blind spots in standard analysis and questions underlying assumptions. This can be influenced by biases such as group think or mirror imaging.
For the imaginative thinking technique, I picked scenario building. Scenario building encourages analysts to explore different future possibilities, which helps overcome biases such as anchoring. Anchoring is where one relies too heavily on initial information. By imagining various scenarios, analysts can better anticipate unexpected developments.
Regarding the impact of technology and AI on intelligence analysis, Hare and Coghill (2016) discuss how future analysts will need different skills compared to those pre-9/11. The rise of big data and machine learning has shifted the analytical landscape from purely human-driven processes to a hybrid where analysts must now harness the power of AI to process vast amounts of data efficiently. Future analysts will require less emphasis on memorizing data and more on interpreting complex information patterns, integrating diverse data streams, and employing advanced computational tools (Hare & Coghill, 2016).
The skills necessary for effective intelligence analysis in the future will be fundamentally different from those used by analysts before 9/11. As technology evolves, the analyst’s role will increasingly involve directing and refining the outputs of AI systems. This necessitates a strong grounding in both the technology and the domains to which it is applied. This evolution mirrors bigger shifts across knowledge bases. Integration of technological and human judgement will become critical to managing increasingly complex global threats and opportunities (Gartin, 2019).
-Brad
References:
Hare, N. and Coghill,P. (2016, January). The future of the intelligence analysis task. Intelligence and National Security, https://doi-org.ezproxy2.apus.edu/10.1080/02684527.2015.1115238
Gartin, J. W. (2019, June). The Future of Analysis. Studies in Intelligence. https://www.cia.gov/static/8bdbc27e6a29bf09201ccdaf45677a61/Future-of-Analysis.pdf
Response #2 (Dennis): Which of the 12 U.S. Government (2009) Structured Analytic Techniques do you think best enable analysts to reduce cognitive and perceptual biases? Analysis of Competing Hypothesis is difficult to allow natural biases to influence the outcome of the analysis (Moe, 2016).
Pick one diagnostic, one contrarian, and one imaginative thinking technique and describe why you chose those three.
Diagnostic-Analysis of Competing Hypothesis
I like this approach because it’s methodical and takes a lot of time because it requires a lot of effort, but the product is better. It will evaluate multiple hypotheses that will result in collecting data. It requires critical thinking which is a common way to think when it comes to performing at a higher level. It helps look at all options and will result in better thought-out decisions.
Contrarian-Team A/Team B
I like this concept because there are two separate views. One team is working towards a common goal, and they value teamwork. While team b is trying to compete against team b. This will become beneficial in larger work organizations. With this approach there must be maturity, but it will address weakness in the dynamics of working groups.
Imaginative-Outside-in Thinking
This is used to identify the full range of basic forces, factors, and trends that would indirectly shape an issue (Warner, 2022). This approach is good because the focus is on the focus of what the customers want. It will help with being more connected with customers who support what the organization is doing. I feel like it’s an unself way to enhance their internal perspectives to further advance their cause.
In the article, The future of the intelligence analysis task by Hare and Coghill (2016), they describe how technology and artificial intelligence will impact the intel analysis function. Do you think the skills necessary to be an effective intelligence analyst in the future will be fundamentally different than those used by analysts just before 9/11? I think it will be different because technology is ever evolving. When things evolve that means there must be more and improved ways of training.
Kiss, M. (2016, October 31). Analysis of competing hypotheses (ACH). Medium. https://theiconic.tech/analysis-of-competing-hypot…
Warner, C. (2022, January 26). Structured analytic techniques in Cyber Threat Intelligence. Medium. https://warnerchad.medium.com/structured-analytic-…
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