Global Prescience

"Looking for a lesson in humility? Stand at a major historical marker, and try drawing a perfectly reasonable, prudent conclusion about where that marker is pointing. Believe me, if you read about a 15th century traveler saying, "I have to get back to Italy now; the Renaissance is starting," you're reading a line from a Woody Allen story. Real life rarely offers such prescience, even from the people paid to deliver it…History comes with its very own Doppler effect: as our point of observation changes, so does our understanding of what we are seeing." Jeff Greenfield

The Oxford English Dictionary defines prescience as “knowledge of events before they happen; foreknowledge.” As a human faculty, prescience is known as foresight. The underlying processes of prescience are change processes, that is, the study of change in terms of its locale and causes. Prescience is also the study of how quickly change occurs and its projected consequences (OED).
On a broader scale, global prescience may be construed as trend identification via socio-cognitive and technological networks that point to global trends. In this sense global prescience:
* Specifically focuses on the issues, methods, and philosophies involved in detecting clues, via networks of people and technologies, which point to global trends. In this sense global prescience is a network-centric information processing approach to foresight and detection.
* Explicitly processes and interprets information relevant to the future from multiple perspectives embedded in a network, including art, philosophy, and science. In this sense global prescience relies heavily upon the strong and loose ties across knowledge domains for detecting and predicting global trends.
* Tackles, in parallel, a holistic, networked array of trends and trend-related variables including technology, culture, and the physical environment. It explicitly takes into account the interrelationships of trends, factors and variables within a larger system. In this sense global prescience addresses the global unit of analysis as a network of variables in and of itself.
* Is a human activity driven by the motive to do good or lead human activities toward a great good that has global impact. As such, global prescience is mindful of the need to generate and manage networks of priorities to accomplish good.
* Takes into account long time frames and long term life cycles of ecosystems of global magnitude. In sum, global prescience is a macro-level, network-centric information processing approach to foresight and detection. Global prescience is also related to situation awareness situation awareness and semiotics semiotics
Global Prescience as Trend Identification
Those who think seriously about the future immediately encounter the baffling complexity of the world, with its myriad of factors and forces that interact in seemingly infinite subtle, obvious, and contradictory ways, and challenge attempts to detect and predict future outcomes. The ability to detect emerging trends is important on several levels. Large-scale trends are complex and may have significant, even global impact. Specifically, broad trends can impact the way different segments of society experience important aspects of life, such as the rapid decline in fertility rates around the world due to the availability of contraception and family planning programs, globalization of commerce, aging populations, and the rise of religious extremism.
While it is clear that trend identification is an important activity, attention needs to be drawn to its complexity. A trend may be understood as a pattern of occurrences associated with a system of factors, variables, or components. Such a system “is complex when there are strong interactions among its elements, so that current events heavily influence the probabilities of many kinds of later events.” The extent to which interactions in a system are dense determines the complexity of a system, rather than the number of its individual components. A system with only a few components can still be complex given that patterns of interaction maybe intense. Interaction is also not static as the intensity of interaction may alter across time.The dynamism and density of component relationships therefore lead to unpredictable unforeseen outcomes. Understanding complexity requires input from multiple sources. Complexity is “the interdisciplinary understanding of reality as composed of complex open systems with emergent properties and transformational potential”
The importance of global prescience, prescient sensemaking, and clue detection
The ability to detect emerging trends is important in several respects. Using networks of people and technology, many modern organizations either have or are seeking to embed (with varying degrees of success) future trend detection capability, as with the crucial role of actuaries in insurance companies. Clue detection and similar environmental scanning activities, involve the acquisition and use of information about events, trends, and relationships in an organization’s external environment, the knowledge of which may assist managers in planning future actions Research suggests that organizations deploying systematic scanning activities tend to outperform non-scanning firms.
There are also a growing number of centers and institutes dedicated to analyzing and predicting future trends. In sum, predicting the long term future is increasing in both popularity and importance.
Large-scale trends are complex, potentially ambiguous, dynamic, and frequently interconnected and may have significant, even global impact. Some trends, such as global climate change, represent significant threats, even to the survival of individuals, groups, organizations, and humanity itself. Other trends point to probabilities of events of massive or global impact, such as major cataclysmic occurrences like the global financial panic or the crash of the internet. Lesser threats, such as increases in cybercrime, have the potential to disrupt society. The impact of potential undesirable future events or trends can be emotional, financial. Certain forms of global prescience may be credited with providing early-warning signals to look for indicating the likelihood of certain outcomes taking place and what organizations might do to avoid, mitigate, or cope with such outcomes.
Broad trends can also impact the way different segments of society experience important aspects of life. For example, the National Center for Policy Analysis identifies several demographic trends that have broad implications. These include issues such as implications of an aging American citizenry, a shortage of elderly caregivers, and the rise of single child families.
Detection of clues which may potentially become broad trends may also used to identify opportunities. Examples include the rapid spread of social and interactive technologies is leading to a different mindset towards consumer marketing. Understanding how consumers think and capturing this dialogue that occurs through “chats, blogs, emails, phone calls, and social networks ” will be an important tool for companies interested in developing products that meet their future market demands.
Those engaged in prescient sensemaking may play a key role as change agents. Certain forms of prescient sensemaking seek change, using predictions of the future to transform the present. Futurists, for example, seek to help individuals, groups, and organizations move from a “default future,” which is used, disowned or criticized, to a more desirable future.
The Technology of Trend Identification
Against a backdrop of such complexity, methodological approaches that seek to detect trends have increasingly focused on technical components, and its automation. Research suggests the need for automation given the volume of digital information that renders it impossible for a full reliance on manual detection. At the same time, any one individual can only have a certain source of domain expertise which makes it likely that important pieces of information are not detected. Computational developments have resulted in methodologies that will eventually lead to fully automated trend detection systems that rely heavily on networks of sensors and diverse data sources. Such methods may include tracking visual or sequential variations across time. However, in identifying environmental trends, evidence suggests technical difficulties associated with the detection of long-term linear trends, including the size of trend to be detected, the time-span of available data, and extent of data variability. Clearly, the degree of complexity associated with trend identification depends at least on the substantive nature of the trend, and data sources.
The Significance of Socio-Cognition in Trend Identification
However, it is also critical that social processes and appropriately configured social networks be taken into account when identifying trends, and understanding how trends may have a combinative effect. A hint of how difficult it is to understand the interactive impact of trends is noted by Heifetz and Linsky (2002, p. 13) who make the following observation:
"Every day, people have problems for which they do, in fact, have the necessary know-how and procedures. We call these technical problems. But there is a whole host of problems that are not amenable to authoritative expertise or standard operating procedures. They cannot be solved by someone who provides answers from on high. We call these adaptive challenges because they require experiments, new discoveries, and adjustments from numerous places in the organization and community."

Social processes and networks are important drivers that fuel the process of trend identification. Evidently, methods of trend identification that rely only on automation will be lacking in the interpretive requirements of understanding how trends combine, and the role that social processes play in addressing trends. A solely automated process will lead to a potentially erroneous understanding of trend development.
Global Prescience and Sensemaking
The notion of prescient sensemaking focuses on a general set of activities associated with interpreting and understanding future events and outcomes. Prescient sensemaking is a future-oriented process involving the general sensemaking subprocesses of scanning, interpreting, and acting. Global prescient sensemaking focuses on future-oriented processes at the macro or global level of analysis. Scanning involves information gathering and engaging in search activities. Interpretation requires imputing existing information with structure for the derivation of meaning. Finally, action requires a response that is dependent on the earlier processes of scanning and interpretation. Within a framework of understanding future trends, such action should be viewed as action towards addressing adaptive challenges. Sensemaking is an especially appropriate perspective to understand the process of trend identification. A cognitive approach in understanding sensemaking is supported by research on cognition involved in intuition. Research suggests that managerial executives are hardly passive in making decisions but actively engaging in sensemaking. A potential research avenue is to approach sensemaking using cognitive constructs.
Prescient sensemaking thus takes many forms, including a fundamental recognition that there is an underlying chaos that requires some means of organization . In scanning the environment, an expression of sensemaking includes the act of “noticing and bracketing.” An aspect of the environment is demarcated for further cognitive processing, and such demarcation of the environment may be affected by an individual’s mental model of what is unusual in the environment. A further expression of sensemaking is that of labeling. Labeling results in agreement amongst a set of actors such that further dialogue about what has been labeled can take place. Sensemaking is also action oriented in that sensemaking seeks to answer the question “What do I do next?” Dialogue and communication is fundamental for action to be meaningful action is otherwise part of the underlying chaos. Sensemaking is expressed as a series of conversations embedded with organizations and their structures.
Prescient sensemaking seeks to foresee and evaluate the future on multiple time scales, from the relatively short term of months to a few years, to several years, to decades, to centuries and beyond. This perspective seeks to extend the current future orientation of sensemaking activity, rather than the retrospective nature of sensemaking. Evidence suggests that the amount of time invested in seeking out information leads to a changed perception that leans towards viewing an issue as a threat while seeking out information that is diverse reduces the perceived threatening nature of an issue. This suggests that time itself plays an important role in the outcomes of sensemaking.
Prescient sensemaking also occurs at multiple levels of analysis, including the individual, group, and organization level. Sensemaking is a social process . Sensemaking occurs on an individual level. For example, individuals engage in individual sensemaking activity when they seek to understand the impact of strategic change on their role in the organization. Further, individual sensemaking does not necessarily lead to organizational sensemaking. For organizational sensemaking to occur, social aspects of sensemaking are particularly important. Individuals attempt to make sense of their interpretations by seeking the interpretations of others as well as seeking to influence the interpretation of others through sensegiving. It is suggested that a similar process of influence may occur at a group level. For example, a model of collective turnover where an individual’s negative perception of an organization may be transformed into group perception through group sensemaking.
The more specific process of clue detection refers to identifying small, subtle or lead indicators before they become broad or even global future trends or noting signs indicating the outcomes of known future trends. With respect to the future, many researchers and analysts have focused their efforts on identifying and defining “big” problems and possible solutions. Clues, however, are weak or subtle signals used to identify and define trends or major events before they occur and may be used to predict the emergence, direction, and magnitude of trends and their outcomes. There is also a propensity to identify clues as early warning signals and disseminate them rather than focus on the methods used to identify these clues.
A clue detection engine, as referred to here, is defined as socio-cognitive as well as socio-technical system designed to recognize clues that foreshadow future events or trends. Such engines are devised to bring the social, cognitive, processessual, and technical sides of sensemaking into a coherent package. Our emphasis will be on the socio-cognitive given the importance of social processes in sensemaking.
Sensemaking: The Role of Mental Models and Transactive Memory in Interpretation
While interpretation is usually investigated on an individual level, we suggest that that interpretation may also be done on a group level to enhance overall cognitive resources. One particularly important point of leverage is the development of a group transactive repository. This refers to configuration or network of individual memory systems such that there is a shared sense of how information is distributed amongst individuals. Such cognitive interdependence in how information is encoded, stored and retrieved minimizes the loss of important details . Specifically, “through the encoding and information allocation processes, individual memories become progressively more specialized and are fashioned into a differentiated collective memory that is useful to the group”. Our attempt to address the cognitive processes of sense making in developing a global-level clue detection engine for trend detection thus also responds to a call for research that identifies the domains and contexts under which knowledge that is distributed or common will affect group performance. The need for such research phrased cogently:
“Generating group capabilities involves more than simply assembling a group of individuals with a wide range of specialized knowledge. Although this knowledge base may establish a strong foundation for a successful group, actual group performance depends upon how well the individual members are able to tap into the assembled knowledge base and how well the individual members are able to reconfigure this knowledge base in new situations. Transactive memory, a group’s awareness of the location of knowledge resources distributed throughout the group, provides a promising approach for future study of knowledge and expertise in groups.”
A further cognitive mechanism that will help shed light on the process of sensemaking in trend identification is mental models. Shared mental models are ‘‘knowledge structures held by members of a team that enable them to form accurate explanations and expectations of the task’’ . Further, mental models are used to selectively remove inconsistent information so that other aspects of the environment can be noticed. Importantly, mental models not only render meaning to the social environment but also serve as “a frame of reference for action and interpretation of the world” Overall, trend identification may be understood as the process of updating existing mental models as new information is noticed. A potential research direction is the extent to which mental models overlap amongst individual sensemakers while engaging in the clue detection process of interpretation. Understanding the impact of mental model overlap offers an interesting departure from attempting to detect anomalies which focus on identifying unusual events.
A Network of Sensemakers
Finally, we seek to advance the perspective that sensemakers are entrenched in networks that have the capacity to enhance the ability of individuals in the network to detect trends. This is already a view that exists in relation to “wicked problems” which are difficulties that tend to be unstructured, cross-cutting, and relentless. Wicked problems are unstructured in that causes and effects of such problems are very difficult to pinpoint, leading to complexity and potential conflict due to a lack of consensus. Wicked problems are cross-cutting in that they affect multiple stakeholders each with different perspectives. Finally, wicked problems cannot ever be fully addressed at any point. Wicked problems therefore bear qualities that are highly similar to large-scale trends which arise out of multiple confluences of events, impact diverse communities, and seem to be emergent across time without endpoints. It is argued that while networks are advantageous in terms of information transfer, two potential challenges are highlighted: the need to find ways such that knowledge can be distributed, received and integrated across network participants to address problems, and that failure to allow for the knowledge of others in the network will affect the problem solving potential of networks. Again, these are problems that sensemaking clue detection engines are likely to encounter. We propose that mental models and transactive memories of sensemaking networks will offer insight into how these challenges can be addressed. We further suggest that a network model of sensemakers is useful as it will potentially identify sources of leverage and difficulties that sensemakers will encounter as they interact as a community.
The building block of global prescient social networks and teams of sensemakers is obviously the “sentinel”. A “sentinel” is a specialized type of prescient sensemaker. The sentinel role serves as a gatekeeper between past and present, and explicitly leverages past and present data, and social networks, to predict long term future outcomes. A sentinel is generally in the position to set opinion and may be viewed by others as a thought leader in their field. They also tend to be experts able to probe deeply into specific areas of interest, but utilize some form of peripheral vision, that is, the capability to see, access, assess, and assimilate information outside their specific domain of expertise. A sentinel may relay upon others for peripheral vision. They may sense clues that others miss and bring intellectual wisdom to observable patterns.
A typical understanding of sentinels is that they are individuals tasked with the responsibility of being watchful for an anticipated event . We suggest that watchfulness is a necessary component of trend identification; sentinels should be seeking out interpretable patterns. The context of such watchfulness is necessarily fraught with ambiguity, uncertainty, and complexity given the oceans of information available today.
Not everyone is a sentinel. To distinguish sentinels from other future-oriented sensemaking roles, the following typology is proposed: prescient sensemakers (individuals such as lay people who attempts to make sense of the future in daily living; the focus is on short timeframes and local issues), precogs (individuals who seek to identify clues in environment that may fundamentally change society; such individuals are likely to have limited social influence), actuaries (experts in evaluating the likelihood of events, designing creative ways to reduce the likelihood of undesirable events, and decreasing the impact of undesirable events that do occur. Reducing financial impact of prophets (individuals who make predictions about future events in this world that involve metaphysical variables. Such individuals may claim access to inspiration and divine influence for information; tendency to focus on religious outcomes), and futurists (individuals who specialize in studying and predicting long term future events. They are experts in future trend analysis and prediction with emphasis on the secular), experts (individuals who specialize in a field of study which equips them to induce trends from scientific data and deduce trends from theory), and fortune tellers (individuals who specialize in predicting the future for monetary gain; such future prediction is done on a personal level, and may be performed for entertainment or amusement.
Equivocality as a sense making context suggests that sensemaking sentinels need to have a tolerance for ambiguity and an appreciation for environmental differentiation as potential levers for equivocality. Tolerance for ambiguity refers to the perception that ambiguous situations are desirable while environmental differentiation refers to the degree to which multiple dimensions are applied in understanding the environment. Applied to the notion of global prescience, sentinels who appreciate that understanding how global trends interact with each other necessitates a worldview that tolerates and appreciates ambiguity are more likely to be able detect clues in the environment that ultimately lend themselves to appropriate interpretations of the environment. Sentinels are also individuals who choose to rise above ethnocentrism, in spite of an awareness that countries compete against one another. Sentinels do not specifically look out for national interests per se but seek out global interests. To do so, sentinels need to be aware of their own biases.
Finally, sentinels should be able to think reflexively and in a less linear fashion. Weick’s (1989) notion of the disciplined imagination is applicable in that sentinels need to be aware of the creative power inherent in metaphorical thinking, rather than focusing on end products. Interestingly, rather than viewing trend identification as a series of logical, deductive steps, sentinels may view trend identification as a delicate balance of both inductive and deductive thinking, coupled with the use of metaphors to harness creative perceptions. Rather than asking “how do I know a trend when I see one?” it may be more useful to seek out metaphors analogous to trend formation for more sophisticated insight.
Global Prescience as Semiotics
Through socio-cognitive factors, global prescience is linked to semiotics, the science of how meaning is constructed and understood. The design of a clue detection engine needs to take into account the role of semiotics. The application of semiotics to global prescience underscores the reinforcement of connotative meanings such that sensemaking networks will detect information along a certain calculus. The study of language and audition recognizes the importance of semiotics, alongside its complexity and philosophical basis.
Global Prescience as Situation Awareness
Situation awareness refers to the “complex set of information that must be maintained in real-time tasks. ” It is the degree to which a system’s design closes an information gap by supporting an operator’s ability to obtain information under changing real-time constraints .Applied to global prescience, situation awareness refers to the degree to which informational and technical support systems (clue detection engines) are able to provide sensemaking networks information in dynamic operating environments of changing trends.

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