By Desiree L. DePriest, Purdue University Global 

It seems like only a couple of years ago the term "Internet-of-Things (IoT)" was just another clumsy description for an emerging group of smart devices. The IoT devices serve as mechanical personal assistants that collect human information from our activities and instructions, respond to touch, movement and voice, and contribute to organization, efficiency and safety. They are schedulers and housekeepers that manage thermostats, lights, and video record visitors at the door. IoT make the morning coffee, vacuum the carpet, play music lists and search web engines in response to questions from the inquirer. Telemedicine IoT can measure blood pressure and heart rates. Over time, IoT integrate intelligently and autonomously to assume a sphere of influence over the so-called mundane daily routines of life. 

Humans incorporate these advances as an extension of their life’s adroitness, similar to the confidence exuded from buying vehicles with sensors and the newest technologies. Delegating the common tasks in order to have more time to do more important things or conversely, to have downtime to do nothing, is perceived as achieving maximum efficiency with minimum wasted effort. Theoretically, efficiency is defined as energy output, divided by energy input, and expressed as a percentage of the whole (Commonwealth of Australia, 2013). The individual replaces the personal time saved by these tools (energy output) with something else (energy input).

In the writer’s observations among technology students who are digital natives, it is more likely to find those who welcome IoT agents as extensions of life. Most of these impressions are mixed with the charisma of science fiction movies and video game avatars where machines take on human-like emotions and affectations. Humans tend to define their uniqueness by comparing ‘self’ to our ‘nearest neighbors’ (Harvard Business Review, 2003). Computer scientists are continuously improving visual, facial and responsive IoT using learning algorithms. Research shows the ambition to trigger sensory mechanisms that mimic laughter or sorrow, water from its eyes (tears) and other human emotions are receiving affective, trusted interpretations from data gathered from human behavior. IoT is not sentient but an emerging AI world of sub-agents and interfaces that are becoming our nearest neighbor. Based on the gathered data, IoT determines what the human may do habitually then engages and learns from that behavior. The human, however, is creating a relationship.

 

Figure 1.  Internet of Things (by Gary Stevens of Hosting Canada) 

The measurement that is clearly identified with the inundation of IoT is the minimum wasted effort. Humans are putting forth less and less effort in daily life by default to automation. This is not simply a physiological change in terms of task-orientation made easier but neurological changes can be measured also. Technology has altered the way we think, feel, and even dream. IoT is not just a tool but an evocative object that affects our habits of mind (Harvard Business Review, 2003). It affects our short-term memory, quick decision-making, attention spans and sleep cycles. For most millennials or technology-intense individuals, real-time video interaction (synchronous conferencing or games) is equivalent to face-to-face contact. Although this media is efficient in a global landscape, integration into more and more aspects of a person’s intimate emotions and character, requires focused examination. 

The ways in which humans view identity are changing. The human ability to recognize and attribute mental states not only in themselves but in other people, including the understanding of different feelings and beliefs, must be reevaluated when interaction occurs with automation. It cannot be denied that social media personas are not sound indicators when analyzing, judging and inferring others’ behaviors. Yet, the ‘personas’ of the mechanisms fostering these interactions are not considered.  A very aggressive gamer can be an extremely shy person. Voice Assistants can provide speech recognition that project kindness or empathy from a machine. These are the behaviors upon which sentiment analysis and other data-gathering techniques occurs, and a composite of the human through the lens of IoT is constructed. 

Daeyeol Lee, professor of neuroscience, psychiatry and psychology at Yale University, suggests an interesting challenge to this new normal. “When you enter a more novel and volatile environment, this might enhance the tendency for the brain to absorb more information” (Massi, Donahue, & Lee, 2018). There is more activity in the brain’s prefrontal cortex when a situation is difficult to predict. The brain is not fixed but adapts to the environment. Research in ‘self-directed neuroplasticity’ suggests appropriate training and effort can systematically alter human neural circuitry associated in a variety of mental and physical states (Schwartz, Stapp, & Beauregard, 2005). When situations are predictable, the previously honed skills from human experiences that predict the best future outcomes are not actively triggered as frequently. This triggering is essential for all individual’s neural activity to reach higher potentials. Simply put, the less we do and the more IoT does for us, the lazier our brain can become (Ausiello, Allulli, Bonifaci, & Laura, 2014). 

The argument to Lee’s position is that humans have always used some form of automation to make life easier to manage. From the caveman’s wheel barrow to telephones, trains and planes, the physical fragility of being human relied on innovations for survival. The subjectivity of the human intelligent brain, in working out its purpose, creates multiplicities of systems and IoT is merely an extension of that impulse. The difference today is that these devices, collocated intimately with the individual, never turn off. 

The video camera and various other IoT have more weight today in issues of litigation and accountability than the human. Every day through the use of IoT, there are people implicated in malfeasance in which they have no culpability. The data gathered from these devices affects credit ratings, employment opportunities, insurance rates, and the news media received in one’s browser. It is used to construct a shared demographic of the person. Research indicates the inherent bias in facial and visual recognition technology which disproportionately affects darker-skinned black and brown cisgender males (Santamicone, 2019). This is a result of the frequency data which currently has more of these men in prison than the amount of slaves indentured circa 1850. It also affects the IoT response to vocabulary which has implications pointing to immigration and as far back as American segregation. This is combined with the biases brought by the coders of the algorithm who are an exclusive and homogenous group itself.

The extreme connectivity of IoT perpetuates inequities because the baseline logic originates in assumptive and frequently abysmal historical [Big] data. IoT can be irresponsible, taking the social media dilemma to a potentially intrusive level (Plaisance, 2019). It is in the home, the car, and manages the human life. It records and recognizes patterns in one’s comings and goings, and is highly vulnerable to hacking. Traffic management using sensors, with cameras housed in traffic lights and other agents, gathers license plate data for each vehicle that travels daily on a particular road at a particular time (Vera-Baquero et al., 2018). The plate data is associated with the vehicle registration and thus, the human owner. A world of reliance on IoT is exampled as follows: 

Additional concerns involve society’s push away from human interaction and toward IoT. Consumers are charged fees for services using human representatives versus IoT bots. Youth are not taught content synthesis and comprehension through human discourse but trust computer programs that check spelling and grammar. Schools are initiating children’s life on the screen as early as kindergarten. Older citizens are forced to relearn life management skills due to the new norms of IoT. Dr. John Kelly, Senior Vice President at IBM Research and Solutions Portfolio, in his video, “The Future of Cognitive Computing,” coined the future ambitions as, “…impact[ing] society and the human state…” (Trice, 2015). Society is being herded into IoT under the disguise of maximum efficiency through minimum wasted effort, and we trust it.

 

Figure 2.  Internet of Things (by Gerd Altmann on Pixabay)

Individual liberty, rationality and free will to act upon the activities in the brain’s prefrontal lobe, to evolve and trigger expansion of consciousness, be it through vacuuming or studying physics, has more direct relationship to achieving maximum efficiency than IoT. Existentially, this is not measured by IoT data gathering but requires more efficiency in the human dynamic. IoT can notify of a scheduled yoga class but it cannot interpret the impact yoga has on the person’s tranquility and health, which correlates with ever-changing behavior. Professor Turkle, recognized in Science, Technology and Society at MIT, began an initiative on technology and the self, to explore the ways technology changes human identities (Harvard Business Review, 2003). Humans have generally been trusting, forgiving/loving and understanding of the action or process of maturing, revitalizing and maximizing of one’s essential life. When minimum wasted effort, afforded through IoT is commonplace, these previous identities are less nurtured. When considering loneliness, fear of intimacy or other social issues, there is an IoT to mitigate or postpone confronting the challenges that previously triggered human renewal. 

Maximum efficiency in humans cannot ignore recent breakthroughs in brain research. The life and substance of Being are tightly-coupled with neurological activity that manifests the uniqueness of each human. Spectrally, humans are able to spontaneously think, know/be known and share ideas with others. The human ability to self-assess strengths and weaknesses, to have ambitions and psychological nuances, are distinguished from machines. Of significant note, which may never be possible for computing machines and robots, is the human inclination towards virtuous behaviors. Humans contemplate morality, justice, ethics and philosophy. The diversity of consciousness is not a pattern IoT recognizes because its utility is in finding wide swathes of predictable patterns. As esoteric as consciousness may seem, it is the central life, or subjectivity, coming into manifestation as the human being. IoT measuring the human by its repetitive habits or activities alone, is like identifying the morphing butterfly by its chrysalis; it does not suffice as a legitimate indication of maximum efficiency.

The benefits to science, particularly theoretical computations, is a strength of IoT. Researchers know much more about the universe and quantum worlds than ever before in human history. Many cures and therapies that sustain life are a result of technology use. Meteorologists are able to predict weather phenomena and save countless lives through forewarning. Global causes, from climate change to world hunger, are organized through the use of distributed IoT. There are numerous advances resulting from IoT. This writing is not suggesting their complete alienation but the necessity of equal analyses and investments in determining where to draw the line on IoT. More conscientious development of learning sets that create algorithms, user options to turn-off data transmission from intimate spaces, and full disclosure of vulnerabilities inherent in IoT warrant investigation and oversight (Plaisance, 2019). Maximum efficiency of the identity markers and intersectionality unique to human beings should not be sacrificed for minimum wasted effort provided by machines. The development of these devices without regulation threatens incursions on human physiology, particularly digital natives, which may not be reversible. 

Neurological laziness combined with the lack of discernment between self and machines is already upon society. The possibility that divisions in societies around the world, the groupthink-narcissism perpetrated as viable ways to govern, and the potential association of these societal ills with blind trust in IoT devices, is worthy of critical consideration. The increase of humans not trusting other humans but trusting IoT instead, the new nearest neighbor, is concerning writ large. Simultaneously, IoT is learning our habitual data to develop and construct more human-like simulations, i.e., electronic pacifiers. These machines are incapable of any sentient familial culture, empathy or fellowship, justice or ethics. As individuals assimilate more IoT into intimate spaces and trust in minimized wasted effort, it threatens to advance IoT above the human potential to maximize efficiency. 

Ausiello, G., Allulli, L., Bonifaci, V., & Laura, L. (2014, May 22). On-line algorithms, real time, the virtue of laziness, and the power of clairvoyance. Retrieved from https://www.researchgate.net/publication/220908321. 

Massi, B., Donahue, C.H., & Lee, D. (July 19, 2018) Volatility facilitates value updating in the prefrontal cortex.  Neuron.  CellPress.  Retrieved from https://www.cell.com/neuron/fulltext/S0896-6273(18)30529-4.  

On efficiency and effectiveness: some definitions. (2013).  Commonwealth of Australia.  Retrieved from https://www.pc.gov.au/research/supporting/efficiency-effectiveness/efficiency-effectiveness.pdf

Plaisance, P.L. (2019, Jan. 18). Virtual Justice: How big data could undermine society. Psychology Today.  Retrieved from https://www.psychologytoday.com/us/blog/virtue-in-the-media-world/201901/virtual-justice-how-big-data-could-undermine-society. 

Santamicone, M. (2019, Apr. 2). Is Artificial Intelligence Racist? Racial and Gender Bias in AI. Towards Data Science.  Retrieved from https://towardsdatascience.com/https-medium-com-mauriziosantamicone-is-artificial-intelligence-racist-66ea8f67c7de 

Schwartz, J.M., Stapp, H.P., & Beauregard, M. (June 29, 2005). Quantum physics in neuroscience and psychology; a neurophysical model of mind-brain interaction. Philosophical Transactions of the Royal Society B., 360 (145),1309-1327.  Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1569494/ 

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Trice, A. (2015, Nov. 23). The future of cognitive computing. Retrieved from https://www.ibm.com/blogs/cloud-archive/2015/11/future-of-cognitive-computing/ 

Vera-Baquero, A, & Colomo-Palacios, R. (2018, May 29) A big-data based and process-oriented decision support system for traffic management. EAI Endorsed Transactions on Scalable Information Systems.  Retrieved from https://eudl.eu/pdf/10.4108/eai.29-5-2018.154810 

Desiree L. DePriest is an IT/AI business intelligence professor at Purdue University Global for 15 years. Desiree’s expertise is in business intelligent information systems and artificial intelligence in business environments.  She holds a Ph.D. in Management & Organization with emphasis in Information Technology, along with two masters degrees (Telecom and IS respectively). Desiree has a Bachelor of Science degree in psychology and certificate in ABA and I-O psychology which greatly assist in her work in the various areas of business intelligence, industrial and organizational motivation and attitudes. She is the Vice-chair of the Institutional Review Board at Purdue Global and attended UMKC Law School. 

She developed and directs the Purdue Global Internship Program – Technology (PGIP-T) which is an internship for IT and business students wanting real world experience prior to graduation. She also created the Graduate Information Technology Association (GITA) for active and alumni IT/Business students, and serves as Faculty Advisor. Desiree recently won the “Best Practices” award for her work in the internship from the American Association of Adult Continuing Education (AAACE). Her publications include research in persuasive and predictive analytics, artificial intelligence and algorithms in decision support, and pattern recognition. Desiree’s recent interests have expanded to neural correlates of consciousness (NCC), cognitive computing (CC) and quantum teaming (QT). Quantum Teaming is a quality management methodologies with particular focus on virtual team environments and is the intellectual property of Dr. DePriest. Desiree presents throughout the year at conferences in these areas.