5 Myths About Artificial Intelligence

By Jyoti Nigania |Email | May 5, 2018 | 6114 Views

Artificial intelligence is the future. Artificial Intelligence (AI) is more widespread from self-driving cars and Siri personal supporters, to chatbots and email forecast agents that will take routine tasks out of human fingers. 

Every organization must have "AI". For the executive trying to make logic of this confusing landscape, being able to distinct the truth from the mythologies in the marketplace is essential. 

AI has the potential to improve lives. But it comes with fears about economic disruption and a brewing "AI arms race." Like any transformational change, it's complicated. Perhaps the biggest AI myth is that we can be poised about its future effects.

  Following are the five myths about Artificial Intelligence:

  •  Distinguish between a machine and a human:

It is positively true that chats with AI chatbots are often unwillingly funny. And no one who relates with Alexa or Siri or Cortana is going to say they pass the Turing Test. "Their responses, often paved collected out of fragments of stored conversations, make logic at a local level but lack long-term consistency." 

But AI is already writing financial news, sports stories and weather reports, and readers aren't noticing. AI is also producing "deep fake" videos from invented speeches by politicians to pornography comprising celebrities computer-generated faces that many people think are real. These rapid advances present vital concerns, shaking the public's confidence in what they see and hear. 

  •  AI will automate the economy and put folks out of work:

Machines are now presented in the system and put folks out of it. Now naturally person thinks that they are jobless due to the emergence of AI which leads poverty.

But in transforming work, AI may also create new jobs. "We can't predict what jobs will be created in the future, but it's always been like that." Historically, technological change has initially diminished, but then later increased, employment and living values by allowing new industries and segments to arise. We don't yet know how AI will affect employ in the long term. Between now and then, there may still be disturbances, and we'll have to deal with the rising breach between those who have the skills to thrive in a moving world and those who don't.

  •  AI can remove human bias from decision-making:

With the involvement of AI, the biasness is separate from the system as the work is now handled by computers. If only it were that simple. In one example that shows AI's weakness to bias, ProPublica found that a program intended to play a key role in criminal justice decisions from bail to sentencing was almost twice as likely to rate black offenders as likely repeat offenders than white defendants. The program also wrongly rated white defendants as low-risk more often than blacks. "It's often wrong and biased against blacks," ProPublica wrote.

  •  Artificial intelligence is a threat to mankind:

Some prominent science and technology influential have raised serious concerns about the consequences of AI for humanity's future. "The danger of AI is much greater than the danger of nuclear weapons by a lot, and nobody would advise that we allow anyone to build nuclear weapons if they want."

The fact is we just don't know where AI will lead us, but that doesn't mean incurable terminators are going to start nuisance the streets. The more pressing concern might not be that AI is a risk to us, but that we're a risk to ourselves if we don't workout carefully in how we push ahead with our AI experiments.

In some situations, AI can save lives. In March, a self-driving car struck and killed a pedestrian in Arizona, an event that foretold trouble for the developing technology. Nevertheless, many researchers have long held that self-driving vehicles will help cut traffic humanities overall.

  •  Need data scientists, machine learning experts, and huge budgets to use AI for the business:

Many tools are progressively obtainable to business users and don't require Google-sized investments. Some types of AI applications do need heavy lifting by Ph.D.s and computational linguists, however, a rising number of software tools that use AI are becoming more accessible to business users. AI technology at one end of the range does require deep skill in programming languages and sophisticated techniques. Most organizations will opt to leverage business applications developed on top of tools that companies such as Google, Apple, Amazon, Facebook, and well-funded start-ups build. T

hat process requires less data science expertise and more knowledge of core business processes and needs.

"Training" an AI is secretive that is often in technical language and considered that it can be only done by data scientists. Other experts are also involved in this procedure.

 Conclusion:

At last one should not trust in the mythologies, should believe in AI. It is part of the inevitable development of how humans use tools and technology. The organisation needs to the chasing of customer service by examining new methods to increase efficiency and effectiveness.  Now the job is to bring that expansion to the next subsequent level.

 

 

Source: HOB