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Exploring Two Approaches to Technology Futures Methodologies

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In the realm of Technology Futures, the objective is not to forecast specific outcomes, but rather to comprehend the possibilities amid various uncertainties. This understanding can be achieved through a series of five structured steps, which we have previously discussed, alongside the four essential components that underpin any inference in Technology Futures as organizational tools. Now, we can focus on the methodologies employed to actively engage with Technology Futures.

We have two primary methodologies available: Backcasting and Visioning. Both approaches facilitate the creation of scenarios or potential futures, grounded in our current knowledge and insights. They are both oriented toward the future and require robust critical thinking. I view both methodologies as normative rather than predictive, and they incorporate scientific reasoning along with creativity and imagination. It's worth noting that these methods can be used independently, but I advocate for their simultaneous application to elucidate the same Technology Future.

To begin, let’s delve into Backcasting. For our illustrative example, I will utilize brain-computer interface (BCI) technology, a field I have researched extensively and remain passionate about. My ongoing interest leads me to consistently gather Signals and contemplate advancements in this technology.

Backcasting involves starting with a desired future outcome and following six defined steps to construct a Scenario.

The first step is to define an objective. I articulate this as a headline, such as “First human receives bidirectional brain-computer interface implant.”

While this statement is speculative, it is grounded in a collection of Signals related to brain-computer interfaces, specifically employing a projective modeling approach.

It is crucial to recognize that there is a nonzero probability that this objective could materialize in some future. At this stage, I do not concern myself with the specific likelihood; rather, my analysis of relevant Signals indicates a continuous progression toward a future where (a) invasive BCI hardware is feasible, (b) bidirectional BCI systems are under development, and (c) social pressures are influencing innovation towards this objective.

Next, we inquire about the goals or milestones necessary to trace a path from the objective back to the present, ensuring the projection remains valid. This leads me to specify goals and constraints.

Goals do not need to be sequentially linked. Instead, they represent conditions that must hold true for the envisioned objective to be achieved. I visualize this process as constructing a brick road in reverse.

In practical terms, I work backwards from the stated objective. In our BCI example, I might outline the following goals and constraints:

  • A bidirectional BCI must be engineered.
  • A receiving component for the BCI must be developed beforehand.
  • Neuroscience must establish a conceptual framework for transmitting a thought from an external source to the receiving brain.

Some goals and constraints directly reflect Signals, which I prefer to start with due to their straightforward nature. Others exist in the whitespace between Signals, presenting a greater challenge and requiring restrained imagination to avoid fabricating unattainable goals. I iterate this process until I establish a coherent linear if-this-then structure from the present to the objective.

Once satisfied, I add a set of subordinate points describing the present. This constitutes the third step in the Backcasting process and must be firmly rooted in Signals to effectively anchor our objective.

For example:

  • Non-invasive BCIs are available commercially, though with low fidelity and limited functionality.
  • Invasive BCIs face deployment challenges due to technological constraints and potential brain damage risks.
  • New Invasive BCI technology (thin, flexible film) was developed and tested in animals in 2015, leading to its first human trial in 2023.

All of these statements reflect the current reality.

Next, in the fourth step, I ask a fundamental question regarding the combined backcasted goals and the present description: what factors are moving Signals from the Present to the stated Future?

This can be complex; we want to avoid reiterating previously stated information. Instead, we aim to encode the causes in exogenous variables, which elucidate observable effects. For instance, what factors are driving the development of new invasive BCI technology (point c in the present description)?

With our goals, present description, and exogenous variables established, we proceed to step five: conducting scenario analysis, which inherently incorporates morphological field analysis.

A scenario describes a potential future state (the object) along with the surrounding systems (the context). Essentially, the scenario narratively facilitates the transition from the present system (3) to the objective (1) through the utilization of goals (2) and variables (4) as narrative elements.

Assuming the objective (1) is attainable, we can explore potential scenarios within our operational contexts (e.g., Military, Civil, Climate) and consider disruptive elements. Morphological field analysis aids in constructing these scenarios.

The procedure for high-level morphological field analysis (adapted from general morphological analysis, per Zwicky) is as follows:

  1. Identify and define dimensions (these represent goals (2)).
  2. Identify dimensional states for each dimension.
  3. Create a matrix using (a) as column headers and (b) as values within those columns.

For instance:

Bidirectional BCI engineering trends Receiving BCI engineering trends
Positive Neutral Negative Positive Neutral Negative
Thought communication protocol Cost invasive BCI vs non-invasive
Theoretical framework Conceptual framework Prototype High High High Low Low High Low Low
Invasive BCI Implanted  
FDA human trials Slow adoption post trials Rapid adoption post trials  

We utilize the matrix to craft what-if narratives. Note that I have intentionally omitted the fourth column from scenario generation to demonstrate that not all dimensions must be included. The set of dimensions should represent what is maximally available for a scenario.

For example:

  • What if receiving BCI engineering trends are positive, directional engineering trends are neutral, and a thought communication protocol theoretical framework is published as invasive BCI enters stage 3 human trials?
  • What if, based on the above, the thought communication protocol emerges in prototype form?

Using the first example, we might derive a foresight as follows:

> Rapid approval of flexible thin film invasive BCI through human trials, paired with favorable receiving channel engineering trends, will disrupt Education by enabling real-time, distributed thought communication of learning content.

Once we have generated a plausible and high-quality scenario, we can conduct an impact analysis. This analysis answers one or more of the following questions regarding at least one what-if scenario from step five:

  • What will happen?
  • What could happen?
  • What will not happen?
  • What cannot happen?

For instance, using the previous what-if scenario:

> Such technological innovation will displace a variety of educational technologies, significantly impacting a major market vertical.

Compiling the Backcasting efforts yields:

> Rapid approval of flexible thin film invasive BCI through human trials, alongside positive receiving channel engineering trends, will disrupt Education by facilitating real-time, distributed thought communication of learning content. This innovation will displace various educational technologies, affecting a significant market vertical.

Having successfully completed the Backcasting process, we now turn to the complementary methodology known as Visioning.

Visioning involves crafting detailed and vivid depictions of desired future states. This methodology encompasses four steps, some of which will feel familiar from the Backcasting process, while others will differ significantly. Let’s explore how Visioning operates.

To start, we select a Change Element and pose a simple question to identify problems. For example, what issues currently arise in relation to Biodigital Convergence?

Our signal analyses can inform the answers to this Visioning question. The systematic steps for this process are as follows:

  1. Frame the question precisely.
  2. Identify relevant signals.
  3. Review signals if analyses exist; analyze signals if not already examined.
  4. Summarize the information.
  5. Interpret the identified problem(s) concerning the Change Element and in relation to other related Change Elements.

Based on these steps, I might identify the following problem: Humans interacting with AI is leading to a decrease in Sense of Agency (SoA).

If signal journaling has been performed effectively, much of the groundwork for this step is already complete. While I will discuss signal journaling in a future piece, it is vital to view problem identification as a form of systematic literature review. However, it may also be helpful to revisit signal sources to reaffirm one’s understanding of the information.

Continuing with a scientific approach, I identify future outcomes using the scientific method known as grounded theory. Grounded theory is a research design often utilized to extract emergent themes from primary data. In this context, the primary data will consist of articles or papers gathered during signal journaling, supplemented by additional research as needed. For example, I might need to investigate literature on Sense of Agency to deepen my understanding of the phenomenon.

The steps of Grounded Theory are:

  1. Segment articles into excerpts through open coding.
  2. Group excerpts into codes with a subsequent round of open coding.
  3. Organize codes into categories by establishing connections between codes using axial coding.
  4. Analyze additional excerpts and compare with codes.
  5. Repeat steps 2–6 until reaching theoretical saturation.
  6. Define the central idea (selective coding).
  7. Document your grounded theory.

Following this, the third step in Visioning is to identify measurable intermediate goals. This should resonate with the goal and constraint specifications in Backcasting, albeit with material distinctions.

For each potential future outcome, we seek the set of goals that must be achieved between now and then to realize that outcome. This resembles specifying goals in Backcasting but with a linear linkage.

This directly leads to the fourth and final step of identifying resources to accomplish those goals. Again, this overlaps with certain aspects of Backcasting, but with a different focus. For instance, we ask: what resources, if any, are necessary to achieve each of the goals identified in the previous step? The answer may involve technologies or trends that do not yet exist, and unlike Backcasting, Visioning operates at the level of Signals. Keep in mind we can infer potential future signals utilizing the whitespace.

Fellow Technology Futurists, these are the two methodologies I employ to mitigate uncertainty and uncover probable future events. While I cannot claim these are the definitive approaches, I recognize that other methodologies resonate with different individuals. However, these methods work for me, and I hope you find value in the insights and examples provided.

I encourage you to share your thoughts with me. In the meantime, best of luck and happy futuring!

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