A old friend shared a link an article about a tool his company is featuring that got me thinking about my life in the first generation of digital / multimedia forensics. When I began, things were a blend of digital and analogue. When I left, just about everything was digital. But, the tools were fairly simple to use, most relying upon slick and friendly user interfaces.
Not so any more it would seem. Now, things are run from the command line. This means the ability to quickly learn new programming languages is a critical skill for the modern analyst. I’m glad I retired when I did.
Individuals, like me, who tend to process language in a holistic, gestalt manner (aka non-verbal autistics), can face challenges when learning programming languages like Python that require a more analytical approach. Programming requires breaking problems down into discrete components and logical steps. This analytical thinking style can feel unnatural and difficult for someone, like me, used to grasping meaning from broader contexts.
For GLPs, the highly structured syntax of programming languages can be frustrating. Python has meticulous rules about whitespace, indentation, variables, and operators that must be precisely followed. Missing a colon or misaligning indentation by a single space can break code. This level of rigidity clashes with our more intuitive grasp of language.
If the industry rapidly shifts to rely on tools necessitating Python skills, gestalt-oriented thinkers could be left at a disadvantage. Reconfiguring one’s thinking and communication patterns to align with programming logic is achievable but involves a massive, conscious effort. Without proper training and support, employees with gestalt tendencies will struggle to adopt new technical capabilities. This could limit their ability to progress and thrive in roles increasingly intertwined with code.
Thinking hypothetically …
For a gestalt-oriented analyst working in the justice system, in a role such as previously held, a sudden shift to investigative tools relying on Python coding could prove highly disruptive. In their role examining case evidence and generating reports, deep programming knowledge was previously unnecessary. Now, with critical systems updated to leverage Python, a fundamental rewiring of their thought process is required.
Early on, the learning curve could lead to mistaken analysis output or missed retrievals. Logical oversights, syntax errors, or misaligned code would produce inaccurate or misleading findings. In a field where details matter, these mistakes could have serious implications. Faulty investigative conclusions drawn from buggy code could negatively impact case outcomes and erode trust in the analyst’s competency.
Unfortunately, the high-pressure justice environment affords little tolerance for ramp-up time. Expectations to produce technical work immediately, before the gestalt thinker has fully absorbed analytical programming concepts, may set them up for failure. Each mistake potentially carries dire consequences for those involved in affected cases.
Proper training and transitional support could mitigate these risks. But without the organization actively fostering the analytical-gestalt bridge, the analyst may flounder. Their career could suffer if unable to adapt. How this scenario unfolds largely depends on the analyst’s own persistence and the organization’s dedication to unlocking the potential of employees with diverse thinking styles.
I know that I did not work in such an organization. I wonder how many analysts out there are GLPs, like me, and are currently struggling with things as technology progresses …
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This simple rule has worked for me as a GLP who has learned how to approach writing computer programs since the early 90's. Calm your mind, then do it again (repeat). Give yourself the chance to build context around what you are trying to do.
This simple rule has worked for me as a GLP who has learned how to approach writing computer programs since the early 90's. Calm your mind, then do it again (repeat). Give yourself the chance to build context around what you are trying to do.