What Are The Biggest Challenges in Artificial Intelligence and How To Solve Them?
Artificial intelligence (AI) is set to change how the world works. Although it’s not perfect, artificial intelligence is a gamer changer.
Artificial Intelligence in the Pandemic Era: Benefits & Challenges
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AI is the main engine of the digital revolution. The COVID-19 crisis has accelerated the need for human-machine digital intelligent platforms facilitating new knowledge, competences and workforce skills, advanced cognitive, scientific, technological, and engineering, social, and emotional skills.
In the AI and Robotics era, there is a high demand for the scientific knowledge, digital competence, and high-technology training in a range of innovative areas of exponential technologies, such as artificial intelligence, machine learning and robotics, data science and big data, cloud and edge computing, the Internet of Thing, 5G, cybersecurity and digital reality.
The combined value – to society and industry – of digital transformation across industries could be greater than $100 trillion over the next 10 years. “Combinatorial” effects of artificial intelligence (AI), machine learning (ML), deep learning (DL), robotics with mobile, cloud, sensors, and analytics among others – are accelerating progress exponentially, but the full potential will not be achieved without the collaboration between humans and machines.
Artificial Intelligence and machine Learning (ML) form the building block of next generation technology. Their innovative capabilities like computer vision, natural language processing, advanced analytics, enable schools and businesses to create insightful data-driven solutions and contribute to the advancement of the global economy.
BIGGEST CHALLENGES IN THE ARTIFICIAL INTELLIGENCE INDUSTRY
Challenge #1 – Bias of AI Algorithms
AI algorithms can show biased results when written by developers with biased minds. Since there isn’t any transparency about how the decision-making processes run in the background, the real users cannot be sure about its fairness. So, this can result in algorithms that yield biased results.
Challenge #2 – Lack of Privacy
Most companies love data and they like to keep it. The privacy of citizens is constantly put at risk when companies collect consumer data without taking any prior permission — and this is made easy with the use of AI. Facial recognition algorithms are widely used across the world to…
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