D2. Facts, Assumptions, Premises & Inferences

Distinguish between facts and assumptions

It is always important to differentiate facts from assumptions so that the results of conclusions are accurate and valid.

Facts are statements for which there are credible support materials or statistics. These describe the state of the world as it is known and recorded and hence are objective in nature. Facts are building blocks of any analysis since they offer a valid ground to draw conclusions and make recommendations.

Assumptions, however, are propositions which individuals accept as true for the purposes of argument without the benefit of hard evidence – more so the evidence presented in Forensic Science. As a result of a lack of information or in the event of uncertainty, they tend to be useful in analytical work as they can be advanced without the need to have all the relevant details. Assumptions are a matter of personal opinion. Thus, they can be problematic if used in this manner without great scrutiny. However, when analytical judgment turns out to be wrong, it is not because the information was wrong. It was because an analyst made one or more faulty assumptions that went unchallenged. This confirms that assumption, if not challenged, can lead to flawed interpretations and incorrect conclusions.

There are several reasons why it is important to make the difference between fact and assumption.

1. First, it avoids confirmation bias. As mentioned earlier, an unchallenged assumption is mistakenly considered a fact, and analysts risk falling prey to confirmation bias.
2. It enhances transparency and scrutiny. When stating assumptions, analyst make their reasoning more transparent. This allows better scrutiny by others and improves the analytical process.
3. It identifies potential weaknesses. When analysts recognise assumptions as potential points of weakness, it enables them to seek evidence that will confirm or reject these assumptions. If analysts revisit and reevaluate assumptions following new information, it will allow them, to maintain analytical rigour.

If analysts fail to rigorously challenge their assumptions, their reasoning may be built on a weak foundation, making their conclusions vulnerable to collapse in the face of new evidence or information. However, by questioning their assumptions, they can enhance the rigour, transparency, and accuracy of their assessments.

Make a logical inference from available premises

Let’s define premises in the context of intelligence analysis. Premises are facts and assumptions used in an analysis. There are different ways to make inferences in reasoning.

Deductive Reasoning: This approach uses facts to reach a new conclusion by asserting: “if this is true, then this is also true”. This method guarantees that conclusions are reached from premises based on facts and that there is no room for subjective interpretation. Still, it is dependent on the fact analysts possess accurate and factual information.

Inductive Reasoning: This method draws broader generalisations from specific observations or pieces of evidence. It is useful to identify patterns and trends, but unlike deductive reasoning, it does not offer certainty as the conclusions go beyond the stated information.

Analysis of Competing Hypotheses (ACH): ACH is a method to evaluate multiple hypotheses against each other and determine the most likely explanation. If analysts compare hypotheses and seek evidence to disprove rather than confirm them, they can mitigate the risk of confirmation bias and enhance the objectivity of their inferences. For more details look at D1. Hypothesis Testing

Situational Logic: This is a common approach in intelligence analysis. Situational logic focuses on a unique context and driving forces behind a situation. With the help of logical antecedents or consequences of events, analysts can infer the motivations, intentions, or potential future actions of the actors involved.

Sensitivity Analysis: Given that assumptions are inherent in intelligence analysis, sensitivity analysis assesses the impact of key assumptions on the final judgment. If analysts question themselves about what could invalidate those assumptions and seek contradictory evidence, they can test the robustness of their inferences and identify vulnerabilities in their reasoning.

Understand the requirement to identify assumptions and assessments as different from fact.

To understand the requirement to identify assumptions and assessments as different from facts, it's important to recognise the distinctions between these three types of information. Here's a breakdown to help you differentiate.

Facts:

• Objective, verifiable information.
• Can be proven true or false through evidence.
• Not influenced by personal beliefs or opinions.
• Usually based on measurable data or direct observations.

Assumptions:

• Beliefs are accepted as true without proof.
• Often used as a starting point for reasoning or decision-making.
• May be based on past experiences or general knowledge.
• Can be conscious or unconscious.
• May or may not be accurate.

Assessments:

• Judgments or evaluations based on available information.
• Often involves the interpretation of facts and assumptions.
• Can be influenced by personal biases, experiences, and values.
• This may change as new information becomes available.

To identify assumptions and assessments as different from facts.

1. Question the source: Is the information coming from a reliable, unbiased source?
2. Look for evidence: Can the statement be verified through data or direct observation?
3. Identify qualifiers: Words like "might," "could," "should," or "probably" often indicate assumptions or assessments.
4. Recognise personal opinions: Statements that express preferences or judgments are likely assessments.
5. Check for universal acceptance: Facts are generally accepted by experts in the field, while assumptions and assessments may vary.
6. Consider the context: Sometimes, the context in which a statement is made can reveal whether it's a fact, assumption, or assessment.
7. Analyse the language: Factual statements tend to be more neutral, while assumptions and assessments may contain emotional or persuasive language.

Practice examples:

1. "The Earth orbits the Sun." (Fact)
2. "I think this project will be successful." (Assessment)
3. "If we increase marketing, sales will improve." (Assumption)

With such skills, analysts are equipped to critically analyse information and make more informed decisions.