Computer Science Knowledge

The job market has seen a notable change due to artificial intelligence implementation.  It has simplified the process for both recruiters and job seekers (i.e., Google for Jobs and applying online). AI-powered engine streamlines the complexity of job hunting by operating information on job skills, salaries, and user tendencies, matching people to the most relevant positions.  Machine intelligence calculates what wages would be appropriate for a particular job, pulls and highlights resume information for recruiters using natural language processing, which extracts relevant words and phrases from text using specialized software.  Another application is an AI resume builder which requires 5 minutes to compile a CV as opposed to spending hours doing the same job.  In the AI age chatbots assist website visitors and solve daily workflows.  Revolutionary AI tools complement people's skills and allow HR managers to focus on tasks of higher priority.  However, Arti...

AI may increase the scope of work tasks where a worker can be removed from a situation that carries hazards such as stress, overwork, musculoskeletal injuries, by having the AI perform the tasks instead.  This can expand the range of affected job sectors beyond traditional automation into white-collar and service sector jobs such as in medicine, finance, and information technology.  As an example, call center workers face extensive health and safety risks due to its repetitive and demanding nature and its high rates of micro-surveillance. AI-enabled chatbots lower the need for humans to perform the most basic call center tasks. Machine learning used for people analytics to make predictions about worker behavior could be used to improve worker health. For example, sentiment analysis may be used to spot fatigue to prevent overwork.  Decision support systems have a similar ability to be used to, for example, prevent industrial disasters or make disaster response more efficie...

In agriculture new AI advancements show improvements in gaining yield and to increase the research and development of growing crops.   New artificial intelligence now predicts the time it takes for a crop like a tomato to be ripe and ready for picking thus increasing efficiency of farming.  These advances go on including Crop and Soil Monitoring, Agricultural Robots, and Predictive Analytics.  Crop and soil monitoring uses new algorithms and data collected on the field to manage and track the health of crops making it easier and more sustainable for the farmers. More specializations of AI in agriculture is one such as greenhouse automation, simulation, modeling, and optimization techniques. Due to the increase in population and the growth of demand for food in the future, there will need to be at least a 70% increase in yield from agriculture to sustain this new demand.  More and more of the public perceives that the adaption of these new techniques and the use of Ar...