More than Semantics? Communication of (Un)certainty via ‘Estimative/Probabilistic Language’

This chapter examines how (un)certainty can be communicated to ‘end-users’, such as to strategic-level policy- and decision-makers. The domain of ‘Estimative’ or ‘Probabilistic Language’ offers most promising routes forward when employed with appropriately placed caveats relating to its deployment. After defining ‘uncertainty’ and eight different interpretative versions, the ‘Ambiguity Problem’ is next engaged head on by this chapter. Qualitative and quantitative areas relating to ‘Estimative’ or ‘Probabilistic Language’ are then raised for consideration, before looking at ways pertaining as to how (un)certainty is specified. Here, the ‘issue of synonyms’, ‘words to ignore’, ‘attempts at quantification’ to ‘standardisation’ considerations feature much more centrally. Examples drawn upon include those from the US Intelligence Community, considering the US ‘father of intelligence analysis’ Sherman Kent’s historic addressing of the ‘Estimative’ or ‘Probabilistic Language’ areas being focused on in this chapter; extending to presenting more contemporary publicly available US National Intelligence Council authored National Intelligence Estimates (NIEs), and how their insights are communicated to top US political leaders in the White House and Congress. Key conclusions and takeaways note that while there might be much ‘fuzziness’ surrounding ‘uncertainty’, greater clarity can be realised and then more effectively communicated on to end-users via using suitably weighted ‘Estimative’ or ‘Probabilistic Language’. In the next chapter, Chap. 6 , different estimative language phrases will be tested together via conducting a Strategic Options Analysis related pair-wise analysis exercise, ascertaining which phrases are compatible or not—thereby offering some potential greater clarity in the communication of (un)certainty, as well as demonstrating how ‘Estimative’ or ‘Probabilistic Language’ can perhaps be better deployed.