Artificial Intelligence – Trends in Academic Research sees focus on specific domains which are attracting a lot of attention.
- Social human-robot interaction driven by artificial cognizance
- Natural language processing
- Image mining and recognition
- Moral uncertainty in artificial intelligence
- Future of artificial intelligence
Above findings, which signify the trends of artificial intelligence in academic research, have been contributed by Enago Editing Services, a leader in Language editing and publication support services. Being a trusted name in the academic research community, Enago has helped numerous authors improve research communications and achieve success in publication. Recently, the editorial community at Enago experienced scholars from across the globe surging in for publications in high-impact factor artificial intelligence journals. “The relentless parade of applications associated to artificial intelligence are unfolding on many fronts”, says Anupama Kapadia, Editor-in-Chief, Enago Academy. She added, “You must know – majority of these applications are an outcome of the breakthroughs in academic research.” With the potential to truly reshape our lives, artificial intelligence has geared up to enter numerous enlightening journals. This article intends to unfold trends in artificial intelligence in the academic research arena, while showcasing what’s on the horizon of applications developed from such remarkable research. For clarity, we have presented the views of authors and researchers, which have been taken from interviews held by Enago.
Almost every publication is billed as a breakthrough in research, and the list of swelling journals keeps growing longer. However, very few of these publications have the potential to disrupt the status quo, rearrange applications we use, and alter the research landscape forever. It is therefore critical that scholarly researchers should understand the trending nature of every subject matter. Enago hereby cuts through the noise and identifies 4 trends in artificial intelligence, and presents a blend of insights that intend to show a clear picture of how research impacts real lives.
Artificial Intelligence Recent Trends –
Trend 1: Social human-robot interaction
Human-robot interaction (HRI) is a field of study dedicated to designing and assessing communications between robotic systems and humans. Research in HRI is targeted at creating an ecosystem of autonomous machines that interact and collaborate with humans in a functional manner. Recent efforts in research labs are intended to formulate intelligent robots that will co-exist with humans. Self driving car, the most popular application of HRI as we know it, effectively coordinates with other drivers and pedestrians on the road. Similarly, assistive technologies are evolving fast by entrenching intense concepts published by research scholars. For instance, a paper published in Springer Tracts in Advanced Robotics, presented a robotic control system with attentional models for balancing trade-offs between HRI and practical task execution. Such methodologies are poised to intensify the degree at which a robot adapts its communication trajectory to the human behavior.
Even though research has propelled HRI to a great extent, we see very less or no advancement in domestic robots for guiding humans in household environments. Researchers have recently started focusing on this aspect of real-time HRI that would facilitate collaboration between robots and humans in exceptionally domestic environments. The most recent ‘Eureka’ moment in a lab was to achieve perfection in training a robot to autonomously optimize objective functions. A research scholar associated with Enago unveiled that majority of today’s HRI centric trajectory-deciding machines treat humans as objects in the form of obstacles. The scholar said, “HRI is about communication, and trajectories should be decided by machines only after a trial to coordinate with humans rather than merely trying to avoid collisions.” She ended saying, “I am excited as I work with some of the brilliant minds in AI, and we are thrilled to make discoveries every next moment.”
Trend 2: Natural language processing
Natural language processing (NLP) is a branch of artificial intelligence dedicated to enhance the ability of computers to understand human language in any form – written or spoken. Computational linguistics forms the backbone of NLP that aims at deriving the wealth of information from the most nuanced form of communication, human language. When asked about the latest discoveries in NLP, a research scholar replied, “Nothing but the very invention of artificial neural networks for modeling nonlinear processes such as human language and its various aspects including syntax, discourse, semantics, and emotions as well.” He also said that they have recently made great strides in contextual translation of languages, while experimenting on technical manuals and support guides. A paper published in a journal of IEEE attempts to identify research ripe for practical exploration and illustrate the combination of NLP with emerging technologies.
Recent advancements in research around NLP intend to explore Convolution Neural Networks for detecting positive/negative sentiments in text. One specific experiment took movie reviews and customer reviews into account for defining the level of satisfaction the users had. Apart from this, part-of-speech tagging and semantic parsing have also filled many gaps in NLP. Speech recognition, the most popular section in NLP has simplified our lives in the form of smartphones assisting us on a multitude of tasks. The next frontier of NLP that awaits entry in journals is natural language summarization, which would autonomously summarize complex reports including retail sales, medical records and weather data.
Trend 3: Image mining and recognition
According to a study by MarTech, more than 2.7 Zetabytes (at least 1 trillion gigabytes) of data exist in the universe today. What’s the proportion of images in this data lake? Here’s a point of reference – by2020, every human being would be creating about 1 megabyte of imagery data every second – experts say. The imperative of extracting relevant information from images is been increasingly addressed by research scholars today. This trending field of research in artificial intelligence has extensive areas of applications including medical, agriculture, remote sensing and industries. The most common application, Google Photos is an amazing example of image data mining that categorizes images based on characteristics such as places, people, things, etc. It has recently incorporated intelligent recognition of visually similar web images. From Google to Tumblr, the rate of advancement in image mining research is evident. A paper published in Applied Artificial Intelligence journal of Taylor and Francis proposes a new approach of adopting image mining for detecting micro-calcification in digital mammograms.
Semantic analysis, an aspect of image mining, is carried out by collecting comprehensive information and correlating it to historical or comparative data sources. While marvelous discoveries uncover brilliant applications for consumers, semantic analysis remains muddledin the academic research reserves. Anupama Kapadia sanguinely responded, “In private discussions with us, many research scholars have shared their sentiments of having seen setbacks due to the language gap. I believe that the renewal of the narrative of progress in research communications needs to start with subject matter expertise of editorial staff.” She further added, “We at Enago consistently take pragmatic steps toward actively shaping the global research community.”
Trend 4: Moral uncertainty in Artificial Intelligence
The switch of a trolley running towards a group of five people has been left for you to control. If the only option given is to divert the trolley towards a single person, whom out of the five will you choose to be injured? This situation exemplifies moral dilemma, which explains moral uncertainty in the best way. Moral uncertainty (or normative uncertainty) in artificial intelligence is the condition where the machine fails to decide and act due to the presence of multiple moral dogmas. The biggest challenge that the research community is trying to counter is preparing the machine to take a probability distribution over options and create a unified preference relation. In a paper Logical Limitations to Machine Ethics with Consequences to Lethal Autonomous Weapons, authors employ mathematical logic to explore limitations in the moral behavior of machines. Similarly, the paper Implementation of Moral Uncertainty in Intelligent Machines published in Minds and Machines argues that the best way to counter moral uncertainty is by designing a computational framework that takes basics of moral philosophy into account.
Experts argue that moral dilemma is incomputable, thus making it a very intricate instance for computers to respond to. However, recent debates have changed the face of emotional intelligence in machines. Humanoid ‘Sophia’, first ever robot to be granted citizenship, has called for strengthening women’s rights – glimpses of psychologically moral values and thoughts. Such stories of inspiration unearth the glorifying journey of research scholars who have brought splendid discoveries on to the horizon.
Trend 5: Future of artificial intelligence
Rapid advancements in artificial intelligence have reshaped our society, supercharged capabilities and enabled cognizant decisions in real-time. Although all these have brought about a radical transformation, the rate of evolution in artificial intelligence is going to be faster in the future. At the same time, the evolution will bring new waves of step changes in machine’s capabilities. Together they will amount to profound implications for the business, industries, economy, and more broadly, our social community. This claim is not a broken hypothetical statement as many research scholars from the most brilliant labs of universities have clarified their vision regarding the future of artificial intelligence.
Headlines create a hodgepodge of artificial intelligence’s promise and peril. As per some of the published articles in journals, the history of artificial intelligence abounds with shots and smashes, extravagant claims and exasperating disappointments. However, the same publications have referred to a glamorous state of artificial intelligence in the future: real-life benefits will slowly shape up with sophisticated applications. As per the views of research scholars in the interview conducted by Enago, artificial intelligence is a technology that will transform almost everything around us – work, life and the globe on a big picture. Whether we will manage to carve a reasonable path in the highly disruptive and distributive era will depend upon how swiftly we adapt ourselves to the changing landscape. Most of the future academic research in the ‘future of artificial intelligence’ would be about answering a few questions. What’s the real meaning of a society where jobs are scarce? How do we plan to deal with privacy issues? Do we really need external intelligence to assist us?
Next chapter of Artificial Intelligence in academic research
The fact that artificial intelligence will lead to the rapture of robots is a subject of fiery debates. In fact, human beings have always intended to be tinkerers. Obligated by the blossoming desire for innovation, mankind’s expedition for artificial intelligence is deeply rooted in its most primitive times. Our burning desire infused with copious imagination has bended the limitations of artificial intelligence, blazing a trail towards an unthinkable reality. Research, the spine of imaginations, has blurred out the boundaries between fiction and reality when we think of artificial intelligence. This rapid advancement in artificial intelligence wouldn’t have been possible without wild-eyed research scholars who have focused wholeheartedly to turn dreams into fruition. What was once thought to live in the realm of imaginations is a real picture today, a phenomenal prospect – artificial intelligence.
We know that the world is advancing at a dramatic pace and everything evolves lightning fast. However, above 4 trends in artificial intelligence are topics of genuine exploration, and are going to be on the spotlight for some time. Scholarly authors must be heedful of such leapfrogging developments, and mentor budding researchers. In short, as these trending topics take hold in the practical world, journals will flourish with enlightening studies. The bottom line: artificial intelligence will have an edge over us, but what we do today, mostly being capriciously curious and passionate, will exemplify reflections tomorrow. Anupama concludes “Change happens abruptly during the transition between eras. We have equipped our task force with immense knowledge to support research scholars in such shifting dimensions.”
In today’s era, it pays to think boldly, to act before opportunity slips away.– Author
Devi Prasad Swain writes keynote articles and insight papers covering the intersection of technology, business and social environment.
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