121. Emergent Global Trends Impacting on the Future Operational Environment

[Editor’s Note: Regular readers of the Mad Scientist Laboratory are familiar with a number of disruptive trends and their individual and convergent impacts on the Future Operational Environment (OE). In today’s post, we explore three recent publications to expand our understanding of these and additional emergent global trends.  We also solicit your input on any other trends that have the potential to transform the OE and change the character of future warfare.]

The U.S. Army finds itself at a historical inflection point, where disparate, yet related elements of the Operational Environment (OE) are converging, creating a situation where fast-moving trends across the Diplomatic, Information, Military, and Economic (DIME) spheres are rapidly transforming the nature of all aspects of society and human life – including the character of warfare.” — The Operational Environment and the Changing Character of Future Warfare

Last year, the Mad Scientist Initiative published several products that envisioned these fast-moving trends and how they are transforming the Future OE. These products included our:

• Updated Potential Game Changers information sheet, identifying a host of innovative technologies with the potential to disrupt future warfare during The Era of Accelerated Human Progress (now through 2035) and The Era of Contested Equality (2035 through 2050).

 

 

 

Black Swans and Pink Flamingos blog post, addressing both Black Swan events (i.e., unknown, unknowns) which, though not likely, might have significant impacts on how we think about warfighting and security; and Pink Flamingos, which are the known, knowns that are often discussed, but ignored by Leaders trapped by organizational cultures and rigid bureaucratic decision-making structures.

With the advent of 2019, three new predictive publications have both confirmed and expanded the Mad Scientist Initiative’s understanding of emergent trends and technologies:

• Government Accounting Office (GAO) Report to Congressional Committees: National Security Long Range Emerging Threats Facing the United States As Identified by Federal Agencies, December 2018

• Deloitte Insights Technology, Media, and Telecommunications Predictions 2019, January 2019

• World Economic Forum (WEF) The Global Risks Report 2019, 14th Edition, January 2019

Commonalities:

These three publications collectively confirmed Mad Scientist’s thoughts regarding the disruptive potential of Artificial Intelligence (AI), Quantum Computing, the Internet of Things (IoT), and Big Data; and individually echoed our concerns regarding Cyber, Additive Manufacturing, Space and Counterspace, Natural Disasters, and the continuing threat of Weapons of Mass Destruction. That said, the real value of these (and other) predictions is in informing us about the trends we might have missed, and expanding our understanding of those that we were already tracking.

New Insights:

From the GAO Report we learned:

Megacorporations as adversaries. Our list of potential adversaries must expand to include “large companies that have the financial resources and a power base to exert influence on par with or exceeding non-state actors.” Think super-empowered individual(s) enhanced further by the wealth, reach, influence, and cover afforded by a transnational corporation.

The rich population is shrinking, the poor population is not. Working-age populations are shrinking in wealthy countries and in China and Russia, and are growing in developing, poorer countries…. [with] the potential to increase economic, employment, urbanization and welfare pressures, and spur migration.”

Climate change, environment, and health issues will demand attention. More extreme weather, water and soil stress, and food insecurity will disrupt societies. Sea-level rise, ocean acidification, glacial melt, and pollution will change living patterns. Tensions over climate change will grow.”

Internal and International Migration. Governments in megacities … may not have the capacity to provide adequate resources and infrastructure…. Mass migration events may occur and threaten regional stability, undermine governments, and strain U.S. military and civilian responses.”

Infectious Diseases. New and evolving diseases from the natural environment—exacerbated by changes in climate, the movement of people into cities, and global trade and travel—may become a
pandemic. Drug-resistant forms of diseases previously considered treatable could become widespread again…. Diminishing permafrost could expand habitats for pathogens that cause disease.”

From Deloitte Insights Predictions we learned:

Intuitive AI development services may not require specialized knowledge. “Baidu recently released an AI training platform called EZDL that requires no coding experience and works even with small data training sets…. Cloud providers have developed pre-built machine learning APIs [application-programming interfaces] for technologies such as natural language processing that customers can access instead of building their own.”

Cryptocurrency growth may have driven Chinese semiconductor innovation. Chinese chipmakers’ Application-Specific Integrated Circuits (ASICs), initially designed to meet domestic bitmining demands, may also meet China’s growing demand for AI chipsets vice Graphics Processing Units (GPUs). “Not only could these activities spark more domestic innovation… China just might be positioned to have a larger impact on the next generation of cognitive technologies.”

Quantum-safe security was important yesterday. Malicious adversaries could store classically encrypted information today to decrypt in the future using a QC [Quantum Computer], in a gambit known as a ‘harvest-and-decrypt’ attack.”

From the WEF Report we learned:

This is an increasingly anxious, unhappy, and lonely world. Anger is increasing and empathy appears to be in short supply…. Depression and anxiety disorders increased [globally] between 1990 and 2013…. It is not difficult to imagine such emotional and psychological disruptions having serious diplomatic—and perhaps even military—consequences.”

The risk from biological pathogens is increasing. “Outbreaks since 2000 have been described as a ‘rollcall of near-miss catastrophes’” and they are on the rise. “Biological weapons still have attractions for malicious non-state actors…. it [is] difficult to reliably attribute a biological attack… the direct effects—fatalities and injuries—would be compounded by potentially grave societal and political disruption.”

Use of weather manipulation tools stokes geopolitical tensions. Could be used to disrupt … agriculture or military planning… if states decided unilaterally to use more radical geo-engineering technologies, it could trigger dramatic climatic disruptions.”

Food supply disruption emerges as a tool as geo-economic tensions intensify. Worsening trade wars might spill over into high-stakes threats to disrupt food or agricultural supplies…. Could lead to disruptions of domestic and cross-border flows of food. At the extreme, state or non-state actors could target the crops of an adversary state… with a clandestine biological attack.”

Taps run dry on Water Day Zero. “Population growth, migration, industrialization, climate change, drought, groundwater depletion, weak infrastructure, and poor urban planning” all stress megacities’ ability to meet burgeoning demands, further exacerbating existing urban / rural divides, and could potentially lead to conflicts over remaining supply sources.

What Are We Missing?

The aforementioned trends are by no means comprehensive. Mad Scientist invites our readers to assist us in identifying any other additional emergent global trends that will potentially transform the OE and change the character of future warfare. Please share them with us and our readers by scrolling down to the bottom of this post to the “Leave a Reply” section, entering them in the Comment Box with an accompanying rationale, and then selecting the “Post Comment” button. Thank you in advance for all of your submissions!

If you enjoyed reading these assessments about future trends, please also see the Statement for the Record:  Worldwide Threat Assessment of the US Intelligence Community, 29 January 2019, from the U.S. Senate Select Committee on Intelligence.

101. TRADOC 2028

[Editor’s Note:  The U.S. Army Training and Doctrine Command (TRADOC) mission is to recruit, train, and educate the Army, driving constant improvement and change to ensure the Total Army can deter, fight, and win on any battlefield now and into the future. Today’s post addresses how TRADOC will need to transform to ensure that it continues to accomplish this mission with the next generation of Soldiers.]

Per The Army Vision:

The Army of 2028 will be ready to deploy, fight, and win decisively against any adversary, anytime and anywhere, in a joint, multi-domain, high-intensity conflict, while simultaneously deterring others and maintaining its ability to conduct irregular warfare. The Army will do this through the employment of modern manned and unmanned ground combat vehicles, aircraft, sustainment systems, and weapons, coupled with robust combined arms formations and tactics based on a modern warfighting doctrine and centered on exceptional Leaders and Soldiers of unmatched lethality.” GEN Mark A. Milley, Chief of Staff of the Army, and Dr. Mark T. Esper, Secretary of the Army, June 7, 2018.

In order to achieve this vision, the Army of 2028 needs a TRADOC 2028 that will recruit, organize, and train future Soldiers and Leaders to deploy, fight, and win decisively on any future battlefield. This TRADOC 2028 must account for: 1) the generational differences in learning styles; 2) emerging learning support technologies; and 3) how the Army will need to train and learn to maintain cognitive overmatch on the future battlefield. The Future Operational Environment, characterized by the speeding up of warfare and learning, will challenge the artificial boundaries between institutional and organizational learning and training (e.g., Brigade mobile training teams [MTTs] as a Standard Operating Procedure [SOP]).

Soldiers will be “New Humans” – beyond digital natives, they will embrace embedded and integrated sensors, Artificial Intelligence (AI), mixed reality, and ubiquitous communications. “Old Humans” adapted their learning style to accommodate new technologies (e.g., Classroom XXI). New Humans’ learning style will be a result of these technologies, as they will have been born into a world where they code, hack, rely on intelligent tutors and expert avatars (think the nextgen of Alexa / Siri), and learn increasingly via immersive Augmented / Virtual Reality (AR/VR), gaming, simulations, and YouTube-like tutorials, rather than the desiccated lectures and interminable PowerPoint presentations of yore. TRADOC must ensure that our cadre of instructors know how to use (and more importantly, embrace and effectively incorporate) these new learning technologies into their programs of instruction, until their ranks are filled with “New Humans.”

Delivering training for new, as of yet undefined MOSs and skillsets. The Army will have to compete with Industry to recruit the requisite talent for Army 2028. These recruits may enter service with fundamental technical skills and knowledges (e.g., drone creator/maintainer, 3-D printing specialist, digital and cyber fortification construction engineer) that may result in a flattening of the initial learning curve and facilitate more time for training “Green” tradecraft. Cyber recruiting will remain critical, as TRADOC will face an increasingly difficult recruiting environment as the Army competes to recruit new skillsets, from training deep learning tools to robotic repair. Initiatives to appeal to gamers (e.g., the Army’s eSports team) will have to be reflected in new approaches to all TRADOC Lines of Effort. AI may assist in identifying potential recruits with the requisite aptitudes.

“TRADOC in your ruck.” Personal AI assistants bring Commanders and their staffs all of the collected expertise of today’s institutional force. Conducting machine speed collection, collation, and analysis of battlefield information will free up warfighters and commanders to do what they do best — fight and make decisions, respectively. AI’s ability to quickly sift through and analyze the plethora of input received from across the battlefield, fused with the lessons learned data from thousands of previous engagements, will lessen the commander’s dependence on having had direct personal combat experience with conditions similar to his current fight when making command decisions.

Learning in the future will be personalized and individualized with targeted learning at the point of need. Training must be customizable, temporally optimized in a style that matches the individual learners, versus a one size fits all approach. These learning environments will need to bring gaming and micro simulations to individual learners for them to experiment. Similar tools could improve tactical war-gaming and support Commander’s decision making.  This will disrupt the traditional career maps that have defined success in the current generation of Army Leaders.  In the future, courses will be much less defined by the rank/grade of the Soldiers attending them.

Geolocation of Training will lose importance. We must stop building and start connecting. Emerging technologies – many accounted for in the Synthetic Training Environment (STE) – will connect experts and Soldiers, creating a seamless training continuum from the training base to home station to the fox hole. Investment should focus on technologies connecting and delivering expertise to the Soldier rather than brick and mortar infrastructure.  This vision of TRADOC 2028 will require “Big Data” to effectively deliver this personalized, immersive training to our Soldiers and Leaders at the point of need, and comes with associated privacy issues that will have to be addressed.

In conclusion, TRADOC 2028 sets the conditions to win warfare at machine speed. This speeding up of warfare and learning will challenge the artificial boundaries between institutional and organizational learning and training.

If you enjoyed this post, please also see:

– Mr. Elliott Masie’s presentation on Dynamic Readiness from the Learning in 2050 Conference, co-hosted with Georgetown University’s Center for Security Studies in Washington, DC, on 8-9 August 2018.

Top Ten” Takeaways from the Learning in 2050 Conference.

100. Prediction Machines: The Simple Economics of Artificial Intelligence

[Editor’s Note: Mad Scientist Laboratory is pleased to review Prediction Machines: The Simple Economics of Artificial Intelligence by Ajay Agrawal, Joshua Gans, and Avi Goldfarb, Harvard Business Review Press, 17 April 2018.  While economics is not a perfect analog to warfare, this book will enhance our readers’ understanding of narrow Artificial Intelligence (AI) and its tremendous potential to change the character of future warfare by disrupting human-centered battlefield rhythms and facilitating combat at machine speed.]

This insightful book by economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb penetrates the hype often associated with AI by describing its base functions and roles and providing the economic framework for its future applications.  Of particular interest is their perspective of AI entities as prediction machines. In simplifying and de-mything our understanding of AI and Machine Learning (ML) as prediction tools, akin to computers being nothing more than extremely powerful mathematics machines, the authors effectively describe the economic impacts that these prediction machines will have in the future.

The book addresses the three categories of data underpinning AI / ML:

Training: This is the Big Data that trains the underlying AI algorithms in the first place. Generally, the bigger and most robust the data set is, the more effective the AI’s predictive capability will be. Activities such as driving (with millions of iterations every day) and online commerce (with similar large numbers of transactions) in defined environments lend themselves to efficient AI applications.

Input: This is the data that the AI will be taking in, either from purposeful, active injects or passively from the environment around it. Again, defined environments are far easier to cope with in this regard.

Feedback: This data comes from either manual inputs by users and developers or from AI understanding what effects took place from its previous applications. While often overlooked, this data is critical to iteratively enhancing and refining the AI’s performance as well as identifying biases and askew decision-making. AI is not a static, one-off product; much like software, it must be continually updated, either through injects or learning.

The authors explore narrow AI rather than a general, super, or “strong” AI.  Proclaimed Mad Scientist Paul Scharre and Michael Horowitz define narrow AI as follows:

their expertise is confined to a single domain, as opposed to hypothetical future “general” AI systems that could apply expertise more broadly. Machines – at least for now – lack the general-purpose reasoning that humans use to flexibly perform a range of tasks: making coffee one minute, then taking a phone call from work, then putting on a toddler’s shoes and putting her in the car for school.”  – from Artificial Intelligence What Every Policymaker Needs to Know, Center for New American Security, 19 June 2018

These narrow AI applications could have significant implications for U.S. Armed Forces personnel, force structure, operations, and processes. While economics is not a direct analogy to warfare, there are a number of aspects that can be distilled into the following ramifications:

Internet of Battle Things (IOBT) / Source: Alexander Kott, ARL

1. The battlefield is dynamic and has innumerable variables that have great potential to mischaracterize the ground truth with limited, purposely subverted, or “dirty” input data. Additionally, the relative short duration of battles and battlefield activities means that AI would not receive consistent, plentiful, and defined data, similar to what it would receive in civilian transportation and economic applications.

2. The U.S. military will not be able to just “throw AI on it” and achieve effective results. The effective application of AI will require a disciplined and comprehensive review of all warfighting functions to determine where AI can best augment and enhance our current Soldier-centric capabilities (i.e., identify those workflows and processes – Intelligence and Targeting Cycles – that can be enhanced with the application of AI).  Leaders will also have to assess where AI can replace Soldiers in workflows and organizational architecture, and whether AI necessitates the discarding or major restructuring of either.  Note that Goldman-Sachs is in the process of conducting this type of self-evaluation right now.

3. Due to its incredible “thirst” for Big Data, AI/ML will necessitate tradeoffs between security and privacy (the former likely being more important to the military) and quantity and quality of data.

 

4. In the near to mid-term future, AI/ML will not replace Leaders, Soldiers, and Analysts, but will allow them to focus on the big issues (i.e., “the fight”) by freeing them from the resource-intensive (i.e., time and manpower) mundane and rote tasks of data crunching, possibly facilitating the reallocation of manpower to growing need areas in data management, machine training, and AI translation.

This book is a must-read for those interested in obtaining a down-to-earth assessment on the state of narrow AI and its potential applications to both economics and warfare.

If you enjoyed this review, please also read the following Mad Scientist Laboratory blog posts:

Takeaways Learned about the Future of the AI Battlefield

Leveraging Artificial Intelligence and Machine Learning to Meet Warfighter Needs

… and watch the following presentations from the Mad Scientist Robotics, AI, and Autonomy – Visioning Multi-Domain Battle in 2030-2050 Conference, 7-8 March 2017, co-sponsored by Georgia Tech Research Institute:

Artificial Intelligence and Machine Learning: Potential Application in Defense Today and Tomorrow,” presented by Mr. Louis Maziotta, Armament Research, Development, and Engineering Center (ARDEC).

Unmanned and Autonomous Systems, presented by Paul Scharre, CNAS.

76. “Top Ten” Takeaways from the Learning in 2050 Conference

On 8-9 August 2018, the U.S. Army Training and Doctrine Command (TRADOC) co-hosted the Learning in 2050 Conference with Georgetown University’s Center for Security Studies in Washington, DC.  Leading scientists, innovators, and scholars from academia, industry, and the government gathered to address future learning techniques and technologies that are critical in preparing for Army operations in the mid-21st century against adversaries in rapidly evolving battlespaces.  The new and innovative learning capabilities addressed at this conference will enable our Soldiers and Leaders to act quickly and decisively in a changing Operational Environment (OE) with fleeting windows of opportunity and more advanced and lethal technologies.

We have identified the following “Top 10” takeaways related to Learning in 2050:

1. Many learning technologies built around commercial products are available today (Amazon Alexa, Smart Phones, Immersion tech, Avatar experts) for introduction into our training and educational institutions. Many of these technologies are part of the Army’s concept for a Synthetic Training Environment (STE) and there are nascent manifestations already.  For these technologies to be widely available to the future Army, the Army of today must be prepared to address:

– The collection and exploitation of as much data as possible;

– The policy concerns with security and privacy;

 – The cultural challenges associated with changing the dynamic between learners and instructors, teachers, and coaches; and

– The adequate funding to produce capabilities at scale so that digital tutors or other technologies (Augmented Reality [AR] / Virtual Reality [VR], etc.) and skills required in a dynamic future, like critical thinking/group think mitigation, are widely available or perhaps ubiquitous.

2. Personalization and individualization of learning in the future will be paramount, and some training that today takes place in physical schools will be more the exception, with learning occurring at the point of need. This transformation will not be limited to lesson plans or even just learning styles:

Intelligent tutors, Artificial Intelligence (AI)-driven instruction, and targeted mentoring/tutoring;

– Tailored timing and pacing of learning (when, where, and for what duration best suits the individual learner or group of learners?);

– Collaborative learners will be teams partnering to learn;

Targeted Neuroplasticity Training / Source: DARPA

– Various media and technologies that enable enhanced or accelerated learning (Targeted Neuroplasticity Training (TNT), haptic sensors, AR/VR, lifelong personal digital learning partners, pharmaceuticals, etc.) at scale;

– Project-oriented learning; when today’s high school students are building apps, they are asked “What positive change do you want to have?” One example is an open table for Bully Free Tables. In the future, learners will learn through working on projects;

– Project-oriented learning will lead to a convergence of learning and operations, creating a chicken (learning) or the egg (mission/project) relationship; and

– Learning must be adapted to consciously address the desired, or extant, culture.

Drones Hanger / Source: Oshanin

3. Some jobs and skill sets have not even been articulated yet. Hobbies and recreational activities engaged in by kids and enthusiasts today could become occupations or Military Occupational Specialties (MOS’s) of the future (e.g., drone creator/maintainer, 3-D printing specialist, digital and cyber fortification construction engineer — think Minecraft and Fortnite with real-world physical implications). Some emerging trends in personalized warfare, big data, and virtual nations could bring about the necessity for more specialists that don’t currently exist (e.g., data protection and/or data erasure specialists).

Mechanical Animal / Source: Pinterest

4. The New Human (who will be born in 2032 and is the recruit of 2050) will be fundamentally different from the Old Human. The Chief of Staff of the Army (CSA) in 2050 is currently a young Captain in our Army today. While we are arguably cyborgs today (with integrated electronics in our pockets and on our wrists), the New Humans will likely be cyborgs in the truest sense of the word, with some having embedded sensors. How will those New Humans learn? What will they need to learn? Why would they want to learn something? These are all critical questions the Army will continue to ask over the next several decades.

Source: iLearn

5. Learning is continuous and self-initiated, while education is a point in time and is “done to you” by someone else. Learning may result in a certificate or degree – similar to education – or can lead to the foundations of a skill or a deeper understanding of operations and activity. How will organizations quantify learning in the future? Will degrees or even certifications still be the benchmark for talent and capability?

Source: The Data Feed Toolbox

6. Learning isn’t slowing down, it’s speeding up. More and more things are becoming instantaneous and humans have no concept of extreme speed. Tesla cars have the ability to update software, with owners getting into a veritably different car each day. What happens to our Soldiers when military vehicles change much more iteratively? This may force a paradigm shift wherein learning means tightening local and global connections (tough to do considering government/military network securities, firewalls, vulnerabilities, and constraints); viewing technology as extended brains all networked together (similar to Dr. Alexander Kott’s look at the Internet of Battlefield Things [IoBT]); and leveraging these capabilities to enable Soldier learning at extremely high speeds.

Source: Connecting Universes

7. While there are a number of emerging concepts and technologies to improve and accelerate learning (TNT, extended reality, personalized learning models, and intelligent tutors), the focus, training stimuli, data sets, and desired outcomes all have to be properly tuned and aligned or the Learner could end up losing correct behavior habits (developing maladaptive plasticity), developing incorrect or skewed behaviors (per the desired capability), or assuming inert cognitive biases.

Source: TechCrunch

8. Geolocation may become increasingly less important when it comes to learning in the future. If Apple required users to go to Silicon Valley to get trained on an iPhone, they would be exponentially less successful. But this is how the Army currently trains. The ubiquity of connectivity, the growth of the Internet of Things (and eventually Internet of Everything), the introduction of universal interfaces (think one XBOX controller capable of controlling 10 different types of vehicles), major advances in modeling and simulations, and social media innovation all converge to minimize the importance of teachers, students, mentors, and learners being collocated at the same physical location.

Transdisciplinarity at Work / Source: https://www.cetl.hku.hk

9. Significant questions have to be asked regarding the specificity of training in children at a young age to the point that we may be overemphasizing STEM from an early age and not helping them learn across a wider spectrum. We need Transdisciplinarity in the coming generations.

10. 3-D reconstructions of bases, training areas, cities, and military objectives coupled with mixed reality, haptic sensing, and intuitive controls have the potential to dramatically change how Soldiers train and learn when it comes to not only single performance tasks (e.g., marksmanship, vehicle driving, reconnaissance, etc.) but also in dense urban operations, multi-unit maneuver, and command and control.

Heavy Duty by rOEN911 / Source: DeviantArt

During the next two weeks, we will be posting the videos from each of the Learning in 2050 Conference presentations on the TRADOC G-2 Operational Environment (OE) Enterprise YouTube Channel and the associated slides on our Mad Scientist APAN site — stay connected here at the Mad Scientist Laboratory.

One of the main thrusts in the Mad Scientist lines of effort is harnessing and cultivating the Intellect of the Nation. In this vein, we are asking Learning in 2050 Conference participants (both in person and online) to share their ideas on the presentations and topic. Please consider:

– What topics were most important to you personally and professionally?

– What were your main takeaways from the event?

– What topics did you want the speakers to extrapolate more on?

– What were the implications for your given occupation/career field from the findings of the event?

Your input will be of critical importance to our analysis and products that will have significant impact on the future of the force in design, structuring, planning, and training!  Please submit your input to Mad Scientist at: usarmy.jble.tradoc.mbx.army-mad-scientist@mail.mil.

36. Lessons Learned from the Bio Convergence and Soldier 2050 Conference

(Editor’s Note: Mad Scientist successfully facilitated the Bio Convergence and Soldier 2050 Conference on 8-9 March 2018 with our co-sponsor, SRI International, at their Silicon Valley campus in Menlo Park, California. With over 400 live and virtual participants, our first West Coast conference brought together World class expertise in biology and the tech convergences that will have a significant impact on the changing character of future conflict.)

Bioengineering is becoming easier and cheaper as a suite of developments are reducing biotechnology transaction costs in gene reading, writing, and editing. The Internet of Living Things (IoLT), operating across space and time, and the integration of bioengineering tools (e.g., Genome editing tools such as CRISPR, Talon, ZFN; molecular printers; and robotic strain engineering platforms), big data, high-powered computing, and artificial intelligence are facilitating this revolution. The resultant explosion in knowledge regarding the human body and the brain offers phenomenal opportunities to improve Soldier lethality and survivability. This will be accomplished through improved cognitive and physical skills, as well as maintaining the critical role of human judgement with the ever increasing machine speed we will find on the future battlefield.

1) Prototyping: Innovation has shifted from government demand signals and funding to the incredibly fast paced innovation in the private sector. Emerging products that enhance physical (e.g., Exoskeletons) and cognitive abilities (e.g., Pharmaceuticals) are almost entirely in the commercial sector. The military must determine what is applicable to warfighting and integrate from the commercial space to the defense sector. Prototyping and experimentation will be critical.

2) Personalized Warfare: The mapping of the human genome and the ongoing Human Brain Project offer unprecedented advances in medicine and the neurosciences, but also major vulnerabilities to Soldiers and the homeland. With advanced biological technology evolution comes a host of moral challenges, security vulnerabilities, and new threat vectors. In the future, protecting one’s genomic information will require safeguards similar to how we currently protect our digital identities. We will be more vulnerable to advanced bioweapons and information warfare available to states and non-state organizations.

3) Customization: Advances in biology offer much greater customization in medicine which could improve how quickly our Soldiers learn and how they handle stress and anxiety associated with combat zones. Human 2.0 will have direct Warfighter applications, providing Soldiers with sensory enhancements, human-machine teaming, brains plugged into the Internet of Battle Things (IoBT), and uploadable / downloadable memories. Customization of battlefield medical care will be enabled by advanced diagnostics worn by Soldiers (uniforms and equipment) and eventually embedded. In other countries, we can expect to see the customization of humans with genome editing children to increase height, improve intelligence, and expand creativity.

4) Competition: The democratization of this technology cannot be understated. We will compete with states, non-state groups, and super-empowered individuals who will have access to a full range of human enhancement capabilities and genetic editing tools. China is at parity with the US in this space, but more willing to take technologies to clinical trials.

5) Ethics: The full range of bio tools will be available in the US. They will initially be approved because of their disease curing properties and the ability to improve quality of life for an aging population. They will then be normed into our population. We can expect to see a Soldier enter a recruiting station after some kind of physical enhancement in the next decade, if not sooner. In the Deep Future, the concept of personhood will be challenged.

Mad Scientist is producing a range of products to transfer what we learned from the Bio Convergence and Soldier 2050 Conference out to the Army. We will have videos of the conference presentations posted online here within 10 days, as well as several podcasts posted at Modern War Institute, starting on 28 March 2018. The Bio Convergence and Soldier 2050 Conference Final Report will be posted here within 45 days.

Note that the associated SciTech Futures Bio Convergence Game remains open until 16 March 2018 — share your ideas on-line about the future, collaborate with (and challenge) other players, and bid on the most compelling concepts in this online marketplace.

Read our Mad Scientist Soldier 2050 Call for Ideas finalists’ submissions here, graciously hosted by our colleagues at Small Wars Journal.