What to Expect From Artificial Intelligence

To understand how advances in artificial intelligence are likely to change the workplace — and the work of managers — you need to know where AI delivers the most value.

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Major technology companies such as Apple, Google, and Amazon are prominently featuring artificial intelligence (AI) in their product launches and acquiring AI-based startups. The flurry of interest in AI is triggering a variety of reactions — everything from excitement about how the capabilities will augment human labor to trepidation about how they will eliminate jobs. In our view, the best way to assess the impact of radical technological change is to ask a fundamental question: How does the technology reduce costs? Only then can we really figure out how things might change.

To appreciate how useful this framing can be, let’s review the rise of computer technology through the same lens. Moore’s law, the long-held view that the number of transistors on an integrated circuit doubles approximately every two years, dominated information technology until just a few years ago. What did the semiconductor revolution reduce the cost of? In a word: arithmetic.

This answer may seem surprising since computers have become so widespread. We use them to communicate, play games and music, design buildings, and even produce art. But deep down, computers are souped-up calculators. That they appear to do more is testament to the power of arithmetic. The link between computers and arithmetic was clear in the early days, when computers were primarily used for censuses and various military applications. Before semiconductors, “computers” were humans who were employed to do arithmetic problems. Digital computers made arithmetic inexpensive, which eventually resulted in thousands of new applications for everything from data storage to word processing to photography.

AI presents a similar opportunity: to make something that has been comparatively expensive abundant and cheap. The task that AI makes abundant and inexpensive is prediction — in other words, the ability to take information you have and generate information you didn’t previously have. In this article, we will demonstrate how improvement in AI is linked to advances in prediction. We will explore how AI can help us solve problems that were not previously prediction oriented, how the value of some human skills will rise while others fall, and what the implications are for managers. Our speculations are informed by how technological change has affected the cost of previous tasks, allowing us to anticipate how AI may affect what workers and managers do.



The authors wish to thank James Bergstra, Tim Bresnahan, and Graham Taylor for helpful discussions. All views remain our own.

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Comments (7)
megumi chakma
Artificial intelligence makes our life easy by processing many services. On the other hand, many are feel threated by the artificial intelligence run robotics. It can take the place of the human in the workforces. In term of the high proficiency, accurate works, there is no doubt that artificial intelligence will influence greatly. But, by losing the workspace of human, the consuming power of the human will decrease due to unemployment. I visited a company website titled https://www.namr.com and found many advanced works in different areas.
Theunis Van Niekerk
The shortcoming of predictive intelligence is in the "why" the correlation exists. AI cannot predict if I would choose the red or green apple, unless I select the green or red apple in correlation to another event with a fair amount of consistency. But just because I feel like eating a green apple may not have a correlation. 

AI correlations depend on a high probability that the past to be repeated in the future, which we know is not always the true.
Michael Zeldich
The future is not in AI. Instead it is in artificial subjective systems, capable to work in unconstrained World without any needs in programming.

Designing of the artificial subjective systems will constitute the major leap from machines designed for a purpose to machines designed with abilities.
Jose Miguel Rodriguez
Interesting discussion of AI in the workplace. I agree with your analysis, but I think the most difficult aspect of AI is related to the decision making process. In my experience not only algorithmic approaches solve the task. I used succesfully the heuristic approach for determining the way the succesful manager takes his decisions. I published in my book: How to make your business an intelligent one (only in spanish in Mexico), what I developed as the "Online Advisor", as a result of an AI approach of machine learning.
But nowadays I´ve encountering a lot of problems to replicate this ´cause the succesful  managers are not so comfortable to share their way of making decisons. This is a barrier in actual enterprises.
All well said here.  Q: What about the cultural change that will allow this to happen optimally? If prediction agents force managers to be more (high-level) "people-skilled" -- not simply serve as "mentors" answering questions -- how will businesses move toward training managers to do this?  For decades, businesses have relied on "online learning"/knowledge bases as the answer -- and ignored the soft skills.  But online "knowledge bases" can't replace the training needed to handle/resolve a heated discussion, or address a hostile senior-level audience listening to a proposal for change, or even get users of new IT systems to accept them.  As we often hear, "culture eats (an innovation) strategy for lunch" every single day.  An AI-influenced enterprise will require many steps and plenty of time to align management skills with the needs of the new workplaces.  It would be useful to TEST "the shortest path" to such a new workplace.
Nik Zafri Abdul Majid
AI; in the form of application/system; has definitely helped in decision making and proactive identification of risks for any future projects to be undertaken. It helps in terms of proposed mitigation of problems that haven't even arising yet. But most important, the past datum being input in the system must be something emperical in order to have a proper and systematic simulated model.
Manu Sharma
Absolutely super article Ajay.  Next question would be, how does growth of prediction technologies impact the human workforce, in short and long term. Training requirements for the existing workforce and the changing role of educational institutes in this transformation.