Artificial Intelligence (ANI & AGI) and its impact on society
Recent advancements in AI/ML are mainly due to improvements in processor technologies and cloud data. AI primarily consists of methods that enable computers to mimic human intelligence using logic, if-then rules, decision trees, and machine learning (including deep learning). Deep learning – a subset of machine learning – contains algorithms that permit software to train itself using neural networks. AI can be classified into two categories namely Artificial General Intelligence(AGI) and Artificial Narrow Intelligence(ANI).
Artificial Narrow Intelligence (ANI) & Artificial General Intelligence (AGI)
ANI or Narrow AI refers to AI technologies that mimic narrow aspects of human intelligence. Today, ANI is used in several applications related to Computer Vision, Speech Recognition, and Natural Language Processing(NLP). These applications have a profound impact across different sectors including healthcare, manufacturing, transportation, and many others. Current AI algorithms based on machine learning are very good at accomplishing specific tasks better than humans. For example, image recognition by machines trained via deep learning is better than humans in some scenarios. Recently, Google has demonstrated the use of deep learning for detection of diabetic eye disease.
According to Wikipedia, AGI or General AI is the intelligence of a machine that could successfully perform any intellectual task that a human being can.  Currently, there is no AI technology in this category. Google DeepMind CEO Demis Hassabis along with three co-authors, in a paper published in the journal Neuron, argue that a better understanding of neuroscience is needed to create AGI.  So an interdisciplinary approach is needed for the creation of AGI technology.
Impact of AI technologies
AI technology has the potential to transform many sectors of life. Even though there are many benefits of AI, there are several concerns and issues related to unemployment, system bias, and ethics. On June 26, 2018, US House of Representatives held a hearing on AI titled “Artificial Intelligence – With Great Power Comes Great Responsibility.” 
In this hearing, Fei-Fei Li, co-founder of AI4ALL, stressed the importance of transparency and diversity to address issues related to bias in AI systems. She also called for a “Human-Centered AI” approach with three pillars to tackle some of the problems related to AI. 
Pillar I: AI must be more inspired by human intelligence
Pillar II: AI should strive to enhance us, not replace us
Pillar III: AI must be guided by a concern for its human impact
According to a McKinsey report, 30 percent of “work activities” could be automated by 2030 and up to 375 million workers worldwide could be affected by emerging technologies. Most of the experts in the hearing also emphasized the need of addressing unemployment issue in an increasingly AI-driven economy. Tim Persons, chief scientist at the Government Accountability Office (GAO), said: “Special attention will be needed for our education and training systems, regulatory structures, frameworks for privacy and civil liberties, and our understanding of risk management in general.” 
In summary, identifying the jobs that are at risk due to advanced technologies and retraining the workforce is very critical. Tech industry is also taking some measures to encourage best practices in AI development through “Partnership On AI”.