This article is contributed by our friendly AI from InferKit that uses a deep neural network to generate text automatically. I (human) guided the AI by proposing different subheadings that may be of interest to the reader. Surprisingly, there are many unique perspectives in the article—and some totally wrong “facts”. So, enjoy this fascinating demonstration of artificial intelligence! 🤖
Venture Capital’s hand-picked cream of the crop is teaming up to fight the AI threat with Clearpath
It was a Google Glass moment. The chatter in the room took a sharp turn as soon as Bill Gates entered the door of the packed room at the MIT Media Lab, wearing his usual glasses and bow tie. Most attendees knew that Gates had been in the room the previous night to close a $24 million fund and was a source of inspiration for many of the startups at the conference. His presence, like that of Mark Zuckerberg earlier in the week, sent a palpable message: AI is real. And the people that the world’s largest tech companies and biggest venture funds think can address the most pressing issues will be at the center of the technology’s implementation.
The danger isn’t that a startup hasn’t been funded, but rather that even those companies that have received money could fail. Facebook bought a virtual-reality company for $2 billion only to see it struggle financially. Uber is accused of running a “bad culture,” and although they’ve done much to address their problems, there’s no assurance that an AI startup in 2018 can avoid the same fate.
Three billion dollars later, Google DeepMind, the London-based AI startup in which Gates had a $100 million stake, is transforming health care. The platform AlphaGo defeated the champion of the Chinese game Go, in a move that demonstrated that powerful AI can “outplay” humans in complex games. It also demonstrated that AlphaGo uses deep learning, a tool that Google uses in many of their products to sift through enormous amounts of data and identify patterns and relationships.
Deep learning has captured the imagination of the investment community, and has caught the attention of so-called “venture capitalists,” many of whom know their way around the technology. Some of the top investors in tech, including Sequoia Capital and Kleiner Perkins Caufield & Byers, have also put money into DeepMind.
I had the opportunity to speak with DeepMind CEO Demis Hassabis, who explained that there are many companies today using deep learning to make sense of real-time data and classify how everything from video games to the financial system is doing. Many of these firms, he said, have shown good results, but none of them has changed the world as much as DeepMind has.
“Everything from social networks to gaming is done in a very different way now,” Hassabis said. “In the past, we would just count the number of friends people have on Facebook. Today, we are measuring how people are interacting with each other and with each other’s content. We’re thinking about how much time people spend with each other and the complexity of things people are doing.”
All this is part of the growing trend of AI that has businesses, even non-technology companies, searching for “smart.” For DeepMind, the goal is to help human beings keep up with the change.
“It’s not about how the game of Go is played. We know that games are very different than the way companies actually function,” he said. “We’re very keen to help people and companies adapt to this. That’s what we’re focused on.”
What is Artificial Intelligence?
Artificial Intelligence (AI) is an emerging concept. There is no clear definition as yet for the term, but what we know of it certainly bears little resemblance to what you might have seen on TV in the 1950s.
The idea of artificial intelligence (AI) is rapidly becoming reality. There is no single definition for the term, but what we know of it certainly bears little resemblance to what you might have seen on TV in the 1950s. With the availability of rapidly improving technology, you can expect that by 2040 it will no longer be considered sci-fi.
Like many nascent technologies, the art of AI is based on research into the fundamentals. But rather than use crude logical rules and rules of thumb to determine solutions to problems, AI uses state-of-the-art algorithms to come up with the best solutions based on evidence, data and careful analysis.
A great example of AI’s impact on business was seen in a team that tackled large-scale, time-consuming research. The team were able to look at 5,000 photos on Flickr and identify the popular photos within each category. The computer was able to “think” and find the hottest photos, removing human biases from the process. That sort of work has massive implications for marketers – allowing them to conduct large-scale research and to build out our audience-to-website-viewing processes.
AI is being used in a range of industries, from law and health care to retail and marketing. In marketing, AI is being used to train and shape audience-to-website conversion campaigns. For example, Target Smarty Marketing uses machine learning to improve the performance of their email campaigns by up to 50 percent.
How can AI help with SEO?
AI is already changing SEO. We’ve seen it used to boost indexing and to predict how popular a page may be within a search. As well as predictions for a page’s popularity, AI is also being used to build natural language processing (NLP) capabilities within search results.
Developments in NLP are already enabling companies to incorporate language comprehension, make decisions based on analysis of semantics, and generate more relevant content to rank higher in search engines.
But will it replace human SEO?
It’s likely that you won’t see humans or even a voice at the heart of the search experience, however. This is because the most interesting and useful AI systems rely on large amounts of structured and unstructured data. While NLP, big data and search have brought digital marketing into the 21st century, a more human element of expertise will continue to be critical.
As explained by Adam Davies, digital media and SEO specialist, this will help produce “a sophisticated system that understands and learns the semantic meaning of every online article.” This helps Google to identify trends within articles and predict where to publish your content. Ultimately, this will make it easier for you to reach your audience in an authentic way.
How Does Artificial Intelligence Work?
We all know that Artificial Intelligence is on its way. In recent years, we’ve seen AI systems step in to do things that, in the past, would have been too costly or difficult for human workers to accomplish. And, it’s starting to infiltrate a number of industries, and just because it’s infiltrating an industry doesn’t mean it’s becoming dominant.
Let’s talk about the basic elements of AI and how they work together to create a helpful service or product.
Artificial Intelligence is the science of simulating human intelligence. In the past, AI systems were clunky and artificial and had their limitations. However, that’s all changed thanks to modern AI.
Deep Learning is the process of taking in huge amounts of data and analyzing it to see what kinds of patterns can be created.
A system that uses Deep Learning is one that can learn from the data it is given.
Once the system has a particular pattern it thinks is useful, it can learn from that pattern and then show it to the system and tell it what to do next.
In this way, Deep Learning is a process by which a system can learn from the data it’s given.
Machine Learning is the process of taking in huge amounts of data and analyzing it to see what kinds of patterns can be created.
A system that uses Machine Learning is one that can learn from the data it’s given.
Once the system has a particular pattern it thinks is useful, it can learn from that pattern and then show it to the system and tell it what to do next.
This is an important concept because it shows how Machine Learning is a specific process that can be used to solve specific problems.
Deep Reinforcement Learning.
Deep Reinforcement Learning is the process of training a system in how to function without having a pre-defined set of instructions.
The way it works is that a system is given a set of data, like a cartoon or a picture of a cat, and it’s told to “learn” how to make the cat’s eyes twinkle. The system starts by giving it data about how to change the cat’s eye’s size, and then it has to figure out the rules for how to make the eye twinkle.
What are the Applications of AI?
In recent years, we’ve seen great leaps in Artificial Intelligence. Some of the applications that we see come from voice assistants like Siri or Alexa.
Siri can do tasks like control your smart home devices. Alexa can play music, and control lights.
Another example is self-driving cars. Self-driving cars can be a great way to save lives and lessen traffic, but, when we do see them, they’ll need to be programmed to avoid crashing. It’s because we know from driving that humans aren’t always right.
While many people think that AI will take our jobs, the reality is that AI will take our lives!
Many jobs are on the line, and, while AI will likely never replace a person completely, it will be on par with humans.
Why is AI so Powerful?
One of the main ways that AI can be so powerful is that it will always be learning.
The more that a system is given data, the more it can be trained and, because it’s trained, it will understand more. The more that a system is trained, the better it is at providing you with a solution.
One example of an AI that provides a service is Amazon’s “Alexa.”
The “Alexa” system is a smart assistant that can answer questions, play music, and do a lot of other tasks.
To get “Alexa,” you simply ask it a question, and then it can answer it. So, to order pizza, you would simply ask it “What’s on the menu?” and then it would know what you’re getting and how much it would cost.
Another great example of how AI can be so powerful is the self-driving car.
Self-driving cars are very efficient because they don’t have to worry about people who do stupid things or who don’t follow the rules. Self-driving cars will, with any luck, cut down the number of road accidents.
Also, self-driving cars will not only save lives, they will save tons of time.
How Will Machine Learning Change Our Lives?
We’ve seen a few examples of how AI will change the world, but, with each new use case, the true power of AI becomes more obvious.
We expect to see lots of new jobs created in the future as a result of AI.
While AI won’t completely replace humans, it will become so much better than human intelligence that there won’t be a job that humans cannot do.
How Can You Get Started with Machine Learning?
One great way to get started with machine learning is to use Google’s services.
Google, being such a huge company, has a lot of resources for building things, such as self-driving cars, web search, and more. Google also has tools for teaching machine learning, which are great because they show what different data can be used to teach a machine.
Most people use Google to search for something, and, through Google machine learning tools, they can use their knowledge to teach machines what a search means and how to search.
How Can You Apply Machine Learning?
One great application of machine learning is to give a computer an image of a car, and then have the computer figure out the shape and make it look like a car.
An even better example is teaching a machine how to tell the difference between cats and dogs. You wouldn’t want to give a computer a cat or dog image, right?
This problem can be solved with machine learning, though, because, with enough training data, the machine will eventually learn to tell the difference.
One great application of machine learning is playing games.
Using machine learning, AI can be used to play online games. In order to play online games, the computer would have to have massive amounts of training data.
There are some people who are playing online games with AI on board, and they are getting decent results. This application of machine learning has the potential to be very exciting, and the developers are already working on improving the system.
One final application of machine learning is to create really great customer service.
This application is very powerful because, in a way, it’s like having a virtual personal assistant. The customer service software could be trained by answering customer questions, and the more the customer service software answers the more it will understand about how to provide great customer service.
How Can You Learn More About Machine Learning?
You can check out the machine learning section of Google’s tutorials.
What Are Some Examples of Artificial Intelligence?
Among the many devices and gadgets developed in the past 50 years was the invention of a computer system that could beat the world’s top chess player. But chess is one game.
Other examples of artificial intelligence include intelligent software designed to play other games and play like humans, predictive data analytics that help with forecasting the weather, automated vehicles and the voice-controlled personal assistant, Cortana, built into many of Microsoft’s products.
So which AI is the most useful? Which types of AI are used the most today? And which is still not ready to be used in the workplace? Here’s a look at some of the most talked about AI and the impact it’s having on business and society.
AI has become one of the most prevalent buzzwords in business today. We see it being used in many products and in many different applications. But the type of AI used in the workplace is very different from the type that is being used in non-workplace settings. And the outcomes are very different.
Some forms of AI are designed to process information to make predictions and generate information for others. While these kinds of applications exist, they are far from mainstream. AI applications that enable self-driving cars, face recognition technology, and better voice recognition and translation are becoming more common. These AI-enabled products and services are still far from being completely mature.
The most common use of AI in the workplace is for intelligent software that can perform a task better and more effectively than a person. This application is especially useful in many manual, back-office functions.
In these settings, human workers perform mundane, repetitive, menial tasks that are not easily automated by AI or similar technology. This makes these jobs “cognitive.”
And since these jobs are repetitive, this technology is helping employees be more efficient and productive. They are finding that they are using less time and energy because they are being more productive.
Some of the more common forms of AI in the workplace today are machine learning, natural language processing and conversational interfaces.
What is natural language processing, or NLP?
NLP is the ability of AI systems to understand natural language (which is written and spoken), and answer questions posed to them in a human-like manner. What makes it possible is the combination of numerous technologies, including:
• Natural language processing software (such as that used by Alexa and Siri on smartphones and computers).
• Text-to-speech software (such as that used by your Alexa speaker and Echo).
• Conversation AI (AI software designed to provide dialogue with a human).
What are some other examples of AI being used in the workplace?
There are many other examples of AI being used in the workplace. In some instances, people use AI without knowing it is artificial intelligence. Take the example of point-of-sale (POS) systems that employ an interactive chatbot to assist in solving customer service issues. Or how about a customer-relationship management (CRM) system that uses machine learning to provide recommendations on how to improve relationships between customers and businesses. There are other examples of this happening in the customer service space, including phone-based customer service bots, chatbots that you can interact with via SMS or social media and even telepresence services where workers are connected via telepresence.
Clearly, many forms of AI are already being used in the workplace. And this technology will only increase in the coming years.
Using AI in the workplace isn’t limited to different applications of AI. The development and application of intelligent marketing automation tools is also powered by AI. The application of AI means that marketing organizations are now able to better automate, scale and personalize marketing campaigns based on real-time interactions.
The marketing automation tools and technology that companies are now using include:
- Digital marketing automation tools and services.
- Cognitive platforms, which include AI-powered marketing.
- Predictive analytics platforms.
- Attribution and attribution attribution tools.
So how is it possible for marketing teams to better use AI to run their business?
Through learning data.
Through the use of advanced data analytics.
Through the use of technologies such as AI, cloud computing, predictive modeling, content marketing, customer relationship management, measurement and reporting.
Using these types of AI tools, a company can better measure how different marketing activities (including content, social media, and campaign implementation) are performing.
By being able to better measure and monitor marketing activities, businesses are able to figure out the best strategy for maximizing the performance of each and every marketing activity.
These tools also help companies determine what types of content to use to effectively engage with a given audience. They can also help companies use this data to personalize the content that is provided to customers.
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Where can businesses find more information on artificial intelligence in the workplace?
What Are the Types of Artificial Intelligence?
What do Siri, Alexa, and Google Now all have in common? Each has more than 100 million users, a few thousand developers, and a handful of patents. That’s about as advanced as the first generation of artificial intelligence gets. It may not sound like a lot, but it’s enough to spark an AI revolution. If everything that’s come before it was an evolutionary step towards what’s possible, this next generation will leapfrog us and change everything.
There’s good news and bad news about the latest generation of AI, but it’s not as dire as you might think. The good news is that AI is getting faster and cheaper. The bad news is that much of the learning we’ve done so far will simply fall to the wayside when it comes to making real-world use cases for AI.
How does AI help?
Just like we learned a decade ago that voice assistants like Siri and Alexa can’t understand every command in their native languages, we’re going to hit similar roadblocks in artificial intelligence. Whether it’s to help us protect our cars from hackers, or help us diagnose and treat our cancer with the best available tools, the existing AI technologies will get us so far. But we’re also going to see a leap in “deep learning,” which is a form of AI that makes a machine teach itself by analyzing vast amounts of data.
Deep learning is already being applied to a number of areas, including voice assistants, autonomous cars, and healthcare. In order to make the most out of AI, though, we have to see AI applications in context. In that way, we’ll see AI-based applications that completely change how we work, learn, live, and play. Here’s how you can start to apply AI today.
Any field where you’re dealing with people, and companies or government agencies, people are the biggest bottleneck for innovation. Using AI to help companies improve employee productivity and eliminate waste from their businesses is one example of this.
There are a variety of places where companies can use AI to make employee relations better. One company that’s already successfully applied machine learning to help it manage its employees is Takeaway.com.
Takeaway.com is a leading online takeaway service for restaurants, and it’s particularly interested in how it can optimize ordering process and employee experience. One AI technology, called mSpot, aims to improve customer retention rates by helping managers predict which restaurants will have high churn rates and which ones will be the most successful restaurants, helping them make better business decisions.
Customer retention is high on the list of concerns for many companies, and AI can help address that need. Machine learning can help determine the best retention strategies for a given customer segment, resulting in a more satisfied customer base.
Personalization is an important part of online shopping, and we’re likely to see more of it in the coming years. For example, use of AI to enhance online shopping capabilities could do away with the need for things like checkout bags at the store.
One of the greatest examples of personalization in the online space is Amazon.com’s product recommendations. Amazon’s customer-centric focus has led it to be constantly rethinking the way it does business, and it’s now delivering on its promise to put the customer first. One way it’s doing that is by using AI to improve the customer experience.
Amazon’s recommendation engine, which serves up products based on previous purchases and what the customer is looking for at that moment, is currently powered by a human set of data scientists. One of the biggest changes Amazon made to improve the customer experience was to use AI and machine learning to make recommendations.
Salesforce.com is another company that’s heavily invested in the idea of personalization. Its AI-based Einstein AI platform uses a variety of different techniques, including machine learning, natural language processing, and pattern matching, to improve its various applications, including customer service.
Salesforce is also a leader in social media marketing, using artificial intelligence to analyze sales data and identify patterns and correlations. Its Dreamforce conference, a combination of marketing and sales, is one of the best places to see AI’s impact on sales and marketing strategy in action.
Getting from concept to reality
Most people will probably be surprised at how long it takes to create an AI-based product or service. Companies must first establish a hypothesis and then develop a testable hypothesis before testing the idea and implementing it.
One company that’s already bringing AI to bear in the workplace is Morneau Shepell, an Ontario-based company that offers services for human resources, health benefits, risk management, and pensions. Morneau Shepell recently created an employee assistance program that uses AI to help employees with mental health issues such as depression, anxiety, and stress.
The employee assistance program uses an AI-powered chatbot to send employees the information they need to manage their symptoms. The chatbot helps them decide on the most appropriate support programs and contact relevant experts, so they can get the assistance they need.
As AI technology becomes more mature and widely available, the number of AI-enabled applications will continue to expand. AI has the potential to improve employee experiences in a variety of ways, and that means those companies that invest in AI and machine learning will likely see an improvement in their bottom lines as a result.
What Are Some Famous Applications of Artificial Intelligence?
What Are Some Famous Applications of Artificial Intelligence?
Artificial intelligence is a fast-moving field, and new developments happen frequently. The following are some notable examples of its use.
Machine learning is the ability of a machine to learn from a large data set. For instance, a machine learning system could be trained with historical data to recognize different types of words. It could then learn which words should be linked together into new sentences, and which are linked together into new sentences that are grammatically wrong, or even incorrect. It could also learn the correct way to write each sentence and where the comma belongs. Machine learning allows a machine to learn from lots of data, which it’s able to process much faster than a human.
Machine learning is a relatively new field of study. According to Smart Data Marketing, machine learning is a set of computer science algorithms that allows computers to analyze and interpret data in order to make predictive judgments. The technology is being developed rapidly and is still a nascent field. Its uses vary, but one area in which it is being utilized is for self-driving cars.
Self-driving cars are the future of driving because they are able to take the wheel in the event of an emergency or breakdown. They can also calculate the ideal speed and route, to reach their destination with the least amount of time. This is the type of self-driving technology that companies like Tesla, Uber, and Alphabet are experimenting with. The idea behind it is that the self-driving cars could be the solution to automobile crashes, which kill thousands of people every year. Self-driving cars would not make stupid, reckless decisions that cause crashes. Rather, they will take the lead and avoid accidents.
One example of the way that machine learning works is by running a simulation of hundreds or thousands of real-life cars. The cars run a simulation every time they encounter a certain driving scenario, and it calculates how the vehicles respond to the driving situation. This reduces the amount of time and effort that is needed to create the algorithms for self-driving cars, which should drastically reduce the time taken to create the cars. This speed of innovation will result in self-driving cars being on the road by the end of 2018, with mass production starting in 2019.
Artificial intelligence is the idea of creating intelligent machines. A simple example would be Google Translate, which allows a user to communicate with a foreigner in their own language by translating it into the foreign language and returning the translation.
Google Translate is a good example of an artificial intelligence. It learns from large amounts of data, and its accuracy is better than any human translator. This means that it’s faster and is less error prone than a human translator.
The use of blockchain technology can help any company who wants to make certain transactions safer. A person who is buying a house would only need to show identification and pay a small sum of money. If the house is stolen, the payment won’t be voided because it has already been transferred. The company would then have the ability to track the transfer in real-time to determine whether the property was stolen or not. The entire process is highly secure because it is carried out on a blockchain, and there is no fraud. It’s also secure because the algorithm is extremely secure, and is not based on a centralized, one-size-fits-all database.
Every block on the blockchain is linked to another block. The first block is linked to the previous block, and the previous block is linked to the previous block. It is therefore very difficult to hack a blockchain because there is no single centralized database that can be hacked. The only way to hack the blockchain is to hack all of the nodes on the chain.
The blockchain is also safe because if a person loses their device that is used to store the blockchain, then all of their information on the blockchain can be recovered.
By creating an ecosystem where blockchain is adopted, there will be a change in the way businesses interact with one another.
What’s the Most Powerful Artificial Intelligence Today?
As part of my involvement in the technology space I’m often asked what AI is capable of and when we will see AI making huge changes to society.
As I frequently explain on this blog, if you were to ask someone who doesn’t know anything about AI what it is, I’m sure they would respond “a computer”. If they asked you, “what’s the AI on my phone”, you’d probably answer “Google” or “FaceBook”. This is a joke, but it’s true. AI is becoming so central to our lives that people are starting to equate “AI” with “computers” and fail to see how AI is so much more than that.
Artificial intelligence is a specific field of computer science, so you can imagine my surprise when in 2012, a group of people that have been working on AI for over 60 years decided to convene in San Francisco to discuss AI and discuss their visions for the future.
The group was called the Human-Computer Interaction in the Digital Age Research Group and it included some of the most powerful names in the world of AI, many of whom still work in AI today. While it’s hard to imagine today, during their 60 year careers AI was typically a “boy’s club”, with only men working in it. Since those early days many, including Ray Kurzweil, who heads Google’s AI team, have gone on to found their own start up companies, including Google, Neuralink and Tesla. They now spend their days inventing the future of artificial intelligence, and the field continues to evolve at a rapid pace.
The meeting of AI leaders happened in July 2012. The majority of the group had grown up in the 1960’s and 70’s when AI was still in its infancy. The AI field had its share of ups and downs during the ensuing decades, but the people that I was fortunate enough to spend a few minutes with that day have a lot of experience navigating that first generation of AI and are optimistic about where it is going. This group of extremely bright people believe that AI’s first generation is now largely behind us, and they see a second generation that is already having a significant impact on our lives.
Much of what I learned from this meeting and others that I’ve had the opportunity to attend over the years has led me to develop a perspective on artificial intelligence that I will share in this article. For those of you who think I’m either too bullish or too pessimistic on AI, you should take the time to hear what AI leaders are saying about where the field is headed.
I believe that it will have an incredible impact on the world, with many of the most difficult problems humanity faces in the next 100 years being solved by AI. Just today, Google announced that they have purchased an AI startup that is working to build better video recognition algorithms.
Here are the core reasons why I believe that artificial intelligence will be one of the most powerful transformative technologies of the 21st century, as well as the reasons why I believe that most people misunderstand what AI is and are dangerously underestimating its capabilities.
Smart Devices Will Move Us Out of Virtual Reality, Into Physical Reality
Virtual reality is a form of artificial intelligence that will play an important role in our future. It is useful for games, and immersive environments that reduce the perception of physical distance between you and the digital experiences you are trying to enjoy.
But VR can also be used to fake things that aren’t real. For example, people wear VR headsets to be the pilot of a flying car, and then they spend their time playing the flight simulator. Of course, their body doesn’t experience any of that, so they spend their time staring at a screen, but the experience is actually being simulated and presented to them.
Likewise, the vision-enhancing goggles people wear while wearing their smart devices to enhance their reality and the phones and tablets that they carry in their pockets are also virtual reality. Their bodies are actually doing nothing more than passively observing the data that those devices are displaying. It’s a passive, virtual reality experience, and most people don’t even know that they are part of it.
However, we have seen a tremendous jump in smartphone and tablet operating systems in the last few years. Many of these devices now support telepresence. While this is
Does Strong Artificial Intelligence Exist?
So what are the implications of this for those of us living in a country where some services are now increasingly being offered via online platforms? Will people no longer need to call the doctor, for instance, just to book a doctor’s appointment? Will they use such services less and less?
There is already a range of artificial intelligence services available that can help you book a doctor’s appointment. If these services improve over time, people’s access to them may diminish.
Because the services are automated, they do not involve any interaction with the person booking the appointment. The user only needs to input the information and then leaves the decision making and provisioning to the platform.
An Uber-like service could allow someone to call a private driver to take them to a doctor’s appointment. The appointment could be booked on the platform and then the driver informed, as a courtesy, of the time and place of the appointment. The driver would then be given the destination and told to drive to it.
So far so good, but to book the appointment, the user needs to enter the name and address of the doctor, or an appointment could be made from the platform using the name or address of a practice.
There are other issues, such as reliability and speed of response. The system must be available at all times, which means it must be available at night and during nights when no-one is using it.
These are fairly simple problems that would need to be addressed if automated booking of appointments were to be rolled out. As the process involves transferring the booking to a third party, I am not sure if such a service is being used anywhere else in the world. If not, we could be a trailblazer for the rest of the world.
Would such services enable people to have greater choice when it comes to when and where they seek medical care? Would this enable people to spend more time with their families or loved ones and spend less time in hospital? Could this lead to reduced pressure on our public health system and medical staff?
On the face of it, these are all questions worth exploring, but they raise other issues.
From a budgetary point of view, should it be the job of Government to provide medical care? Or should health care be provided by private enterprise? What would be the effect on other healthcare services in our country?
Should private enterprise be given the opportunity to provide medical care via automated appointment booking systems? Why should the Government bear the cost of the system?
So what’s the answer?
The problem with the current system of booking appointments with GPs is that it can only be accessed by direct phone calls to a practice or GP. This limits the number of potential users.
Perhaps the best solution would be to allow patients to book a doctor’s appointment via email. As email systems are reasonably reliable and faster than telephone systems, many people already make use of this service to make a booking.
Email would not be ideal because patients have no way of knowing if their GP is out of the office or out of the country.
But to improve the situation, we should allow patients to book an appointment on a self-service basis via email. The patient could then either make the appointment directly with the GP or use an online service to make an appointment with a different GP practice.
While it would require some policy-making, it is a question of civil liberties. Should the Government allow private enterprise to offer health care services, or should the Government keep private enterprise in check?
What Year Will Artificial Intelligence Take Over?
Artificial Intelligence (AI) has steadily been becoming an integral part of daily lives in recent years. From Siri and Alexa to self-driving cars, AI is seeing widespread use. By the year 2021, a report by IDC claims that AI will be a $819 billion market with a compound annual growth rate (CAGR) of 28 percent from 2016 through 2021. The report adds that this growth will be the largest growth in computing that will help propel developments in diverse fields such as customer service, medical diagnostics, and self-driving cars.
But as important as AI is to the world we live in today, it is also a conversation worth having that needs to be shared with as many people as possible.
When pondering the potential of AI, there is one group that needs to be brought into the discussion: other children.
Yes, that’s right. As much as AI has become a part of our lives today, we need to realize that we are still in the very early stages of the advancement of AI. A child born today might grow up using a smartphone that doesn’t even exist yet. They might grow up knowing nothing of AI, and that should be a concern for us as we envision the world we are creating for our children.
I recently watched a Facebook video from Outbrain that really got me thinking about this.
In the video, a group of children were asked to imagine that the world had somehow become computerized and as such, all of their conversations would now take place via a virtual assistant. Naturally, they balked at the thought. The teens in the room were even less receptive, though all seemed to give it some serious thought.
Those who resisted the idea were right to do so, and are likely to remain skeptical for the rest of their lives. The vast majority of children are unable to imagine an AI-based world that we are only just beginning to see the beginnings of today. They are also unlikely to see a world that has ever known a world without AI.
In some ways, this should worry us. AI is still very much a young technology, and will undoubtedly evolve and become more and more common in our everyday lives. However, we need to make sure that our children are aware of the possibilities and the potential for positive outcomes that AI can offer. The rest of their lives will be in a world that was predicted years ago, but was so difficult to imagine. If we leave it to chance, we may not be as willing to take the steps necessary to prevent a future filled with technological dystopias.