Artificial Intelligence: 7 Things You Should Know

Content and resources to assist in your understanding and growth within artificial intelligence
Published 09/30/2020
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AI250x250Artificial intelligence (AI) impacts the daily lives of people around the globe. It affects our daily lives in subtle, hidden ways. For instance, AI is used in an increasing number of consumer electronics applications, from children’s toys to Internet of Things (IoT)-enabled household appliances to embedded systems within automobiles for automating driving tasks.

Due to the ever-growing and in-demand field of AI, IEEE and the Computer Society have assembled a variety of content and resources to assist in your understanding and growth within artificial intelligence.

See our top 7 tips and resources for a successful career in artificial intelligence:


  1. Read our Careers in Artificial Intelligence: Advice from an Expert interview with Joanna J Bryson 

    Bryson is a transdisciplinary researcher on the structure and dynamics of human- and animal-like intelligence. She is an associate professor in the Department of Computer Science at the University of Bath and an affiliate of the Princeton Center of Technology Policy. Her research covers topics ranging from artificial intelligence to human cooperation. She holds a Master of Computer Science in Artificial Intelligence and a Master of Philosophy in Psychology from Edinburgh and a PhD in Artificial Intelligence from MIT. Explore her advice, such as figuring out your strengths and focusing on them, predictions, and learning experiences in this “Advice from an Expert” interview.

  2. Stay up to date with IEEE Computer Society’s Top 12 Technology Trends for 2020 

    IEEE Computer Society (IEEE CS) tech experts unveil their annual predictions for the future of tech, presenting what they believe will be the most widely adopted technology trends in 2020. Six of the top 12 technology predictions have been developed into peer-reviewed articles published in Computer magazine’s December issue, covering topics that include cognitive robotics, practical drone delivery, and digital twins. The tech future forecast by the world’s premier organization of computer professionals consistently ranks as one of its most anticipated announcements.

  3. Discover how AI is Helping Marketers Better Engage Customers 

    Artificial intelligence (AI), to use a hackneyed term, is already causing a paradigm shift for marketers. AI, in brief, is helping brands to rapidly collaborate with and learn from online followers. There is an opportunity in the job market in building programs that touch business processes in addition to consumer products. And while there probably exists many a Luddite that deems AI a pervasive jobs threat, the flip side is that it may be a golden opportunity to let the machines do mundane stuff like customer support, enabling humans to become more creative.
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  4. Learn from IEEE Intelligent Systems Magazine’s “AI’s 10 To Watch
    The IEEE Computer Society’s IEEE Intelligent Systems magazine has chosen 10 ground-breakers in artificial intelligence research for its biennial celebration of the “AI’s 10 to Watch” special section.“IEEE Intelligent Systems has long helped promote young and aspiring AI scientists via its biennial “AI’s 10 to Watch” special section. The 2018 group consists of 10 young stars who have demonstrated outstanding AI achievements,” said Qiang Yang, Selection Committee chair and Editorial Board member. “IEEE Intelligent Systems is proud to present these aspiring AI researchers in 2018’s list of ‘AI’s 10 to Watch.’”
  5. Identify how science is seeking to Leverage Artificial Intelligence to Defeat COVID-19Artificial Intelligence and Machine Learning can offer real help against COVID-19. Neosperience created a team of experts working with our technologies to develop screening algorithms that support the health system. With the hashtag #defeatcovid19, Neosperience launched the initiative and community to onboard all organizations and experts in Artificial Intelligence. The goal is to identify technological answers that support healthcare departments and doctors in such a difficult time. The technologies available include neural networks specialized in identifying specific patterns within images and data correlation models. Patterns can be used to support screening and, subsequently, to make the evaluation of therapies more robust concerning the data collected, thus improving the estimation of the prognosis.
  6. Subscribe to IEEE Intelligent Systems magazineIEEE Intelligent Systems serves users, managers, developers, researchers, and purchasers who are interested in intelligent systems and artificial intelligence, with particular emphasis on applications. Topic areas for feature articles include knowledge-based systems, intelligent software agents, natural-language processing, technologies for knowledge management, machine learning, data mining, adaptive and intelligent robotics, knowledge-intensive processing on the Web, and social issues relevant to intelligent systems.
  7. Participate in our Call for Papers: Special Issue on End-to-End System-Level Development and Deployment of Artificial Intelligence before 13 April 2021
    The advancement of AI has accelerated in large part due to the demand for an ever-increasing array of applications providing some level of automated decision-making and human-machine partnering. At the same time, engineers face the challenges of successfully conducting end-to-end system-level development and deployment of AI. For this special issue, we are soliciting articles that address lessons learned and best practices for conducting end-to-end system-level development and deployment of AI. The submissions should tell a story of end-to-end development and deployment in the context of a particular application. Topics of interest for this special issue include, but are not limited to:

      • Development and deployment of AI in embedded systems, the IoT, and the cloud
      • Engineering considerations such as dependability, trustworthiness, explainability, scalability, complexity, ethics, time-to-market, and other factors that influence successful development and deployment of AI-based systems
      • Tools, techniques, infrastructure, and processes that support end-to-end development and deployment of AI-based systems

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