Digital life is augmenting human capacities and disrupting eons-old human activities. Code-driven systems have spread to more than half of the world's inhabitants in ambient information and connectivity, offering previously unimagined opportunities and unprecedented threats. As emerging algorithm-driven artificial intelligence (AI) continues to spread, will people be better off than they are today?
It is predicted that networked artificial intelligence will amplify human effectiveness and threaten human autonomy, agency, and capabilities. The wide-ranging possibilities are, computers might match or even exceed human intelligence and capabilities on tasks such as complex decision-making, reasoning and learning, CX sophisticated analytics and pattern recognition, visual acuity, speech recognition, and language translation. These "smart" systems in communities, in vehicles, buildings, and utilities, on farms, and in business processes will save time, money, and lives and offer opportunities for individuals to enjoy a more customized future.
When it comes to assessment, AI is a part of many candidates and employee psychometric assessments. This can range from realistic chatbot-type conversations with candidates in situational judgment tests (SJT) to proven algorithm-based decisions made from analyzing candidate responses to test questions. The use of AI in assessment is not new. Personality questionnaires have been scored and 'interpreted' by expert-developed algorithms for since long. However, this is just the beginning. AI in assessment is growing at a rapid pace. Most of the companies using AI to give better user experience. Even edTech Platforms like Byju’s using AI chatbots for giving better learning experience to students.
When it comes to AI, one may feel a bit lost in the sea of technical terms—citing a few keywords regarding the usage of AI in assessment.
Robotic process automation: This is achieved by gathering and transferring expert knowledge and then programming the system with an 'if/then' rule-based approach. However, this rule-based system is incapable of learning and improving without being given explicit instructions. Computer-generated interpretative reports in talent assessment are using this technology.
Machine learning: A computer cannot think for itself, but statistical tools can enable a system to make predictions from a given data and to improve its predictions over time. This is used in data analysis to create predictive people analytics to help employers make better talent assessments.
Pattern matching: This AI technique uses the computer to check the sequence of responses to determine if there is a pattern. It can be used to carry out some 'human' tasks, such as recognizing faces or identifying emotions.
Natural language processing: It makes use of text and speech analytics to extract the underlying meaning. This can be applied to analyze speech in interview question responses.
Combining all these aspects, AI plays a crucial role in analyzing and interpreting vast amounts of applicant data.
Beyond these technological considerations, few challenges have to be addressed:
Defensibility: The standardized available 'plug-and-play' AI systems won't differentiate the employer brand. If the competitors use the same systems, they will all be chasing the same talent. Moreover, these systems use 'deep learning networks' that learn as they go. This may sound promising, but it is difficult to explain why an applicant was accepted or rejected. These systems can lead to selection decisions that cannot be defended, making them vulnerable to litigation. Only custom AI systems offer the ability to make transparent and defensible selection decisions.
Time: Custom AI systems mirror human behavior and replicate the best practices of the assessors and raters. To achieve this, the system must be pre-feed with relevant information. It is expected to take up to six months to 'train' an AI system to assess candidates in the same way that the assessors and raters want. Managing this lead time can be a significant challenge.
Ethics: The ethical question is how much support should be taken from an AI system. For example, whether the assessors are happy for an AI system to reject the applicants? Or would they prefer it to flagged as unsuitable candidates to review and check the applicant's details? How to use AI ethically would be a key consideration for many assessors. However, AI's role should be restricted to providing additional information and enhancing efficiency. Assessors should always set the objectives while assessing. AI may then deliver helpful details at various stages of the selection process to arrive at a final decision.
Data handling: AI can analyze vast amounts of data, but the results may be misinterpreted or even deliberately abused. Good data-handling practices will be essential not just for confidentiality but also for maintaining the organization's reputation. AI should be used carefully and honorably to help in predicting the eligible candidates suitable for the role.
There is no reason and no way that a human mind can keep up with an artificial intelligence machine in the future. During the last decade, the use of AIs is also being incorporated into the educational field, whether to support the analysis of human behavior in teaching-learning contexts, as a didactic resource combined with other technologies, or as a tool for the assessment of the students. Is artificial intelligence less than our intelligence?
Find out more about Artificial intelligence on Byju’s.
Digital technology is transforming the modern education sector. In the last ten years, students in universities and colleges have gone from handing in paper essays to uploading them to e-learning platforms.
Students in primary schools are using tablets for classwork and homework. Pupils are designing objects using CAD and printing them with 3D printers. Parents don't have to wait for their children to come home with notes from the teacher; they are posted on hybrid cloud-based platforms that serve as connectivity hubs between parents, teachers and students. These are just a few examples of how technology has changed education. Let's take a closer look at the EdTech software world.
Education is one of the most traditional industries and it is changing nowadays.
Classrooms with a teacher and students don't represent education anymore.
The learning process now tends to leverage EdTech solutions like online classes, learning management systems, and others to make education more effective and accessible.
But how will modern technologies change the way of teaching?
Here at MindK, we did research and found out modern trends which will drive the education sector in 2021.
Man-made reasoning is one of the inexplicable mechanical upsets that has flipped around the showcasing game.
Today, most of the top brands are executing AI to raise their advanced promoting system.
On the off chance that you are searching for approaches to beat your opposition and lead ahead, it is ideal to get a head begin and present it at the earliest opportunity.
To dominate in a quickly evolving market, there are different approaches to utilize AI in business.
One of them is actualizing AI in advanced promoting.
Online teaching helps students to be connected and continued with prescribed syllabus and curriculum.
The Kompanions digital learning experience platform is a consumer-grade learning software designed to create more personalized learning skills and help students discover Individualized learning platforms for schools and institutes.The platform facilitates extensive and comprehensive insights for teacher and learner performances, benchmarking it up against other individuals.
Get in touch with KOMPANIONS today for onboard your institute.
venkat vajradhar Jul 29 · 4 min read Artificial intelligence is not limited to the IT or technology industry; Instead, it is widely used in other fields such as medicine, business, education, law, and manufacturing.In the following, we list the 9 most intelligent AI solutions we use today, presenting marketing machine learning as a present — not the future.SiriSiri is one of the most popular personal assistants offered by Apple on the iPhone and iPad.
The friendly female voice-activated assistant interacts with the user on a daily basis.
She helps us find information, get directions, send messages, make voice calls, open apps, and add events to the calendar.Siri uses machine learning technology to make natural language queries and requests clever and understandable.
CogitoCogito was originally co-founded by Dr. Sandy and Joshua and is the best example of behavioral reform to improve the intelligence of customer support representatives currently on the market.
The company is machine learning and behavioral science to increase customer collaboration for phone professionals.To Know About: Artificial intelligence in the manufacturing market is steadily growing at a CAGR of 49.5%to 2025 and will reach the US $ 17.2 billionCogito applies to millions of voice calls that occur every day.
PandoraPandora is one of the most popular and most demanding technology solutions.
