Understanding the Human-Machine Interface in a Time of Change

Understanding the Human-Machine Interface in a Time of Change

Erica Orange
DOI: 10.4018/978-1-4666-2211-1.ch036
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Abstract

The author presents an overview of how the ubiquitous nature of technology has led to a monumental shift in human evolution – a change involving language, thought, and feeling. The interrelationship between humans and technology will undoubtedly alter the way in which we define what it truly means to be human in a world of complexities. As systems, networks, and programs become more complex, our ability to interface with these machines that play such a prominent and vital role in our day-to-day lives is becoming increasingly difficult. It used to be the human was in charge; able to manipulate the machine to perform a desired outcome. But it is no longer simply about input and output measures. Now the roles are reversing, and it is becoming harder to determine where power and control ultimately resides. Consequently, our ability to manage machines and robots will become more vulnerable. The intimate connection and interoperability of human intelligence with machine intelligence, has undoubtedly impacted the human experience and our process of self-identification.
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Background

Technology is not only getting more demanding, but it is also creating a greater day-to-day human reliance on its functions. In fact, more people are forming attachments to and dependence on non-carbon life forms than perhaps with each other. Technological advances are rapidly engulfing the everyday lives and environments of people all over the globe. There is no doubt that the proliferation of these non-carbon life forms will dramatically affect and alter the ways in which we communicate both with each other and with machines in the future. Knowing how to successfully sustain both kinds of relationships will be essential.

Clearly, machines are becoming increasingly self-sufficient and self-reliant. Robots are not only becoming smarter and more able, but they are also becoming more self-aware and adaptive. In recent years, machines have been developed that learn from observation, similarly to humans who learn from the external environment, and computer programs will increasingly be able to employ its knowledge about emotions to make logical decisions based upon memory. Machines are also able to make inferences about human behavior. In fact, it is predicted that AI-based search engines will become almost humanlike by 2050, and will eventually be able to comprehend users’ questions and queries just like a human assistant. Users will be able to enter questions and get relevant machine-generated answers (The Futurist, 2008.) The development of both mental and emotional robotic intelligence will have profound implications in terms of the way in which humans view their own intelligence. Traits typically assigned to human intelligence, such as abstract thought, self-awareness, reasoning, learning, having emotional knowledge, communication and problem solving will increasingly come under question as artificial intelligences become more advanced.

Key Terms in this Chapter

Geotagging: An application which enables mobile phones to combine social networking and instant messaging with the ability to precisely pinpoint their location on an interactive map.

Connectomapping: A term used to describe the ability to decipher the three-way cyclical intentions between humans, systems and things, thereby creating a comprehensive real-time global map of connections.

Big Syster: A term used to refer to a set of self-contained data systems that will be capable of increasingly pooling their resources and capabilities to create new, more complex and fully independent meta-systems which will offer more functionality, operability and computing power. All of this will be done without human intervention.

Singularity: A future of computer intelligence feeding on itself, becoming smarter at a faster and faster rate.

Technological Singularity: The predicted point in societal evolution when technological progress accelerates beyond the ability of humans to fully comprehend or predict. It can also, more simply, be used to refer to the advent of smarter-than-human intelligence – and the chain reaction of technological advancement to follow.

Non-Carbon Life Forms: Networks, robots, structures, electronic devices and virtual entities.

Othersourcing: The increasing ability to have work done not only off-site and by other entities (such as unanticipated competitors) but by non-humans. In other words, the process of using systems and machines for what humans once accomplished.

Virtual Reality: The tricking of the mind into truly believing it is somewhere else, doing something else.

Avatars: The virtual embodiments of people on screens that can react to your behavior with emotional expressions and interpersonal affect.

Predictive Modeling: The process of using patterns found in past data to identify potential risks and possibilities.

Prifecta: This refers to the union of RFIDs, smartphones and geographic positioning and its direct effect on human privacy. The growth of embedded systems and their interconnectedness raises both major challenges and privacy implications, especially as complex systems are increasingly self-adaptive.

Reality Mining: The collection of technology-based data as it relates to human social behavior.

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