Is AI Going To Be A Jobs Killer? New Reports About The Future Of Work


Amazon announced last week that it will spend $700 million to train about 100,000 workers in the US by 2025, helping them move into more highly skilled jobs. The New York Times observed that with this program Amazon is acknowledging that "advances in automation technology will handle many tasks now done by people." The number of jobs which AI and machines will displace in the future has been the subject of numerous studies and surveys and op-eds and policy papers since 2013, when a pair of Oxford academics, Carl Benedikt Frey and Michael Osborne, estimated that 47% of American jobs are at high risk of automation by the mid-2030s. McKinsey Global Institute: between 40 million and 160 million women worldwide may need to transition between occupations by 2030, often into higher-skilled roles. Clerical work, done by secretaries, schedulers and bookkeepers, is an area especially susceptible to automation, and 72% of those jobs in advanced economies are held by women.

Video: Preparing for the Changes AI Will Bring to Tomorrow's Jobs


As technology fundamentally changes how companies operate, employees will need to hone new skills and build new relationships. On May 23, 2017, the MIT Sloan School of Management hosted the 14th annual CIO Symposium: "The CIO Adventure: Now, Next and… Beyond." The one-day event brought senior IT executives together to discuss key technologies, including IoT, AI, blockchain, Big Data, DevOps, cloud computing, and cybersecurity. The main idea was to help prepare these tech leaders for challenges they face, including shepherding ongoing digital transformations, building a digital organization, and managing IT talent. This series highlights insightful sessions from the event.

Top Trends in HR Practice Powered by Artificial Intelligence, Machine Learning and Virtual Reality


Though businesses are adopting exponential technologies for automating redundant operations and efficiently utilizing enterprise data, HR (Human Resources) has been one of the most important support functions that was not known for espousing much of artificial intelligence, machine learning, deep learning, reinforcement learning, robotics, virtual reality, augmented reality and other powerful tools until now. The impact of the new wave of change brought about by the fourth industrial revolution has been propelling and profound in HR practice too. For more than a decade, I have been involved in talent acquisition, skill building, corporate training and appraisal processes from technology as well as project management side. Though HR has always been an intriguing art for many, the science of it has been a forerunner in captivating my interest. Earlier when enterprises found their HR databases getting inundated with data, making it next to impossible to derive valuable insights necessary for business decisions, enterprises resorted to analytics.

Many Americans feel positive about artificial intelligence, study says


Americans don't fear artificial intelligence as much as is commonly believed, a new study by Gallup and Northeastern University has found. Officials at Northeastern say that it shows higher education should be more involved in training people for the artificial intelligence world.

Reports on the 2013 Workshop Program of the Seventh International AAAI Conference on Weblogs and Social Media

AI Magazine

The program included four workshops, Computational Personality Recognition (Shared Task) (WS-13-01), Social Computing for Workforce 2.0 (WS-13-02), Social Media Visualization 2 (WS-13-03), and When the City Meets the Citizen (WS-13-04). The Workshop on Computational Personality Recognition allowed participants to compare the results of their systems on a common benchmark. Unlike competitive shared tasks, the workshop did not focus just on performance, but rather on discovering which feature sets, resources, and learning techniques are useful in the extraction of personality from text. Organizers provided two gold-standard labeled data sets (released 1 February 2013):, Participants were required to use at least one of the data sets provided by the organizers for their experiments; provide the files used for the experiments; and submit a short paper reporting all the information about features, resources, and techniques used in the experiments, and discussing results.