What is AI? Artificial intelligence has many definitions. The intuitive definition of Artificial Intelligence (AI) by Professor Malone at MIT Sloan School of Management is that AI is “Machines acting in a way that seems intelligent.”
AI can be classified into 2 types:
Narrow AI: This is where a machine can perform one or more narrow tasks in a way that seems intelligent.
General AI: This is where machines can learn and perform a variety of tasks on their own – like a human being.
All applications that exist today are the first type – we can today use innovative technologies to enable machines to perform narrow/well-defined and repeatable tasks very well. There is no practical example of general AI in existence today.
What is collective intelligence?
Collective intelligence is shared or group intelligence that emerges from collaboration. Collective intelligence can also be extended to refer to group intelligence that emerges from a collaboration between humans and machines (human and intelligence & artificial intelligence). Many of the superior outcomes that we see in applications of AI today come from this: humans and machines working together to provide inputs into and learn from each other in order to arrive at superior outcomes.
As a result, effective applications of AI today free up people’s time on tasks that are manual and repetitive (tasks that machines can do best) so that we can focus more on other value-added tasks that require human engagement (tasks that humans can do best).
Artificial intelligence can automate part of the recruiting workflow, especially repetitive, high-volume tasks while providing deeper insights on talent to improve hiring outcomes.
How does this apply in recruitment?
Traditionally, recruitment involves many manual tasks. AI applications can support recruiting by automating most of these manual tasks to free up recruiters’ time to identify & engage with the most relevant talent for a role.
AI applications in recruitment can have many benefits for recruiters including:
Saving time on hiring: Recruiters save time due to the automation of manual or repetitive tasks.
Improving hiring quality: AI can be used to successfully screen applicants, allowing recruiters to focus on the most relevant profiles and engage with them early in the process.
Reduce bias & promote diversity: AI can help collaborators set up and measure all applicants against specific competencies for roles providing a more standardized job-fit evaluation and, hence reducing bias.
Improve retention: AI can help recruiters identify talent that is the right role & culture fit, hence improving employee productivity & retention.
Saving hiring costs: AI can help improve recruiter efficiency and reduce dependence on external agencies to reduce hiring costs by up to 90%.
Snaphunt- leveraging AI to hire quickly & accurately
Snaphunt leverages AI to power your end-to-end hiring: from sourcing, screening, interviewing and collaborating to reference checking and finally hiring the right talent quickly, accurately & cost-effectively.
Automated job descriptions
Save hours of time spent on writing job descriptions from scratch. Our job description generator considers all the elements of the role to create a custom job description for you in a snap!
Benefit from proprietary algorithms to supplement your sourcing with targeted shortlists of applicants that are an experience, skill, competency & motivation fit for the role.
Save time & let our system propose you questions for pre-recorded video interviews based on the skills & competencies you have specified for your role.
AI reference checking
Sit back and let MARTHA – the world’s first AI reference checking assistant collect and conduct reference checks and present you with a report along with an analysis of the reference reliability