Artificial Intelligence

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New technologies for improving healthcare

Various thought leaders have opined that we are in the Fourth Industrial Revolution, as seen by the fact that new technologies are disrupting all industries, disciplines, and economies. By 2020, the digital universe will be 44 trillion gigabytes. This amount is doubling every two years.  Big Data will become so large that artificial intelligence (AI) will make sense of it for us. Already Google has launched the Google Deepmind Health project to scrutinize the data of patients’ medical records and provide better and faster service.

Mitchell Weiss, a robotics safety expert, identified the top three trends impacting occupational health and safety in 2017. They involve complexity of automation, collaborative automation, and complexity of user interface. Along with this there is an increase use of Big Data, artificial intelligence, and IIoT (Industrial Internet of Things) to do medical work.

Internet of Things (IoT) — the ability to connect any device to the Internet through an on and off switch — is a major component of telemedicine, which allows healthcare professionals to communicate with people long distance and provide consultation, diagnosis and treatment of various medical conditions. IOT Telemedicine, which has been gaining in popularity, is now expanding globally.

A Brief Primer on the Internet of Things

Internet of Things is a concept that can apply to things like washing machines, coffee makers, headphones, even parts of machines. The research and advisory firm Gartner estimates  that by 2020, more than 26 billion devices will be connected to IoT. Some analysts say the figure could go as high as 100 billion. In only a short time, our society will be a network of connected “things.” And these “things” include the robots and other devices that are connected to the Internet and can therefore consult with physicians and patients thousands of miles away.

Internet of Things in Healthcare Continue reading

predictive analysis

Predictive Analysis and human behaviour

Predictive Analytics is the branch of machine learning that is putting all the data to work. It takes large data sets and uses mathematical algorithms to form predictive models. Then statistical methods such as regression analysis are used to find the variables that influence the models. Finally, machine learning platforms use those predictive models to find patterns in the past that can allow predictions of patterns in the future.

Human behavior can be seen as a series of patterns that repeat, both individually and as a group, over time. This statistical fact doesn’t negate the possibility of free will; it allows us the use of our free will to repeat patterns of behavior that are most comfortable to us, considering the social, cultural, and family pressures that also influence us.

The analysis of patterns of behavior in humans as a group has been the work of historians, who can look back at great sweeps of time and see patterns that repeat. With the amount of data being collected now through online interactions and geotracking tools such as GPS, machine learning platforms are engaged in how to mine that huge amount of data for the very specific data needed to answer questions.

Predicting the future has been an art in which intuition based on expert knowledge and experience was used to make a predictive analysis. Those who are considered masters in their work combine experience with knowledge, and can see patterns from the past and predict patterns into the future. But we are constrained by the depth and breadth of experience and knowledge we can acquire; we are further constrained by unconscious bias and other human attributes. Continue reading

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Gender Identity for AI

Artificial neural networks have given AIs the functionality for complex problem solving and pattern recognition, and they have entered the workforce, particularly in areas of big data analysis and global finance. As we begin to interact with and study these new learning machines, interesting questions arise. Are they going to take on human behavioral and gender distinctions (gender identity), because they have been programmed with data sets that have unconscious bias? Will those who are giving the learning machines feedback to focus their problem solving allow behavioral constraints into the teaching? If we give the AIs a woman’s voice, and a woman’s name, will we interact with her as if she was a woman? And does that mean she will in turn internalize those social expectations and become more female?

Naturally we are interested in all things having to do with gender. It is the first sentence the world places upon us, when the midwife announces boy or girl. We love gender. We give our teddy bears genders, and can describe in detail why we think-no, why we know that our little darling is a boy or girl. We give our cars genders, names, and personalities. It’s just because we’re human, and we want to humanize the things we love, and that surround us. And part of humanizing inanimate objects is to give them a name, a gender, and shower them with affection.

Part of our fascination with gender has led to some poor science, the popularity of which has trickled down into our collective consciousness. The idea that male brains and female brains are different in a significant way is probably not true, though the debate rages. Structure follows function, and hormones affect the developing brain. But even with minor structural and functional differences in the brains that are most probably hormonally-based, there is very little difference in boys and girl’s brains. There is a much wider variance between individuals than can be measured than between generalized groups based just on gender. We are more complicated than can be described in pop-science about hardwired aggression and nurture vs nature.

What is different between genders is communication, how we use language, and there the gender differences are significant enough to be measured. If we think of communication as the way we input data into our brains, we grow our biological neural networks with the complex range of human communication to which we’re exposed. And there are differences between male and female communication.

So with the science showing that biological neural networks- aka human brains- are more complex than can be measured, but are influenced by hormones, language, biology, and the wide range of human culture, we are left to consider if artificial neural networks will also be influenced by language and human culture. (This is assuming that the artificial neural networks that are biology and hormonally mediated are still a few years in the future.) Continue reading

Bell Curve

The Social Credit Score and the Bell Curve

The Social Credit Score is a system that China has had in trials for several years, and that uses the principles of credit scoring- data streams from several specific sources- to formulate a predictive score. The current credit score uses data from the past to predict future behavior, and allows financial institutions to evaluate risk. The social credit score is taking this model and enlarging it to fields of interest beyond financial behavior.

Some data sources are going to provide information that has a better predictive value for future behavior than others. And while humans often surprise their families and themselves by going off the rails, some patterns of behavior are bound to be repeated. The social credit score attempts to find the behaviors with the best predictive value, and use these values to determine how well a person functions in society.

With a large population, concerns of governments are the needs of the population. And population dynamics are different from tribal, family, or individual dynamics. As the world population grows and human society becomes more complex, we will be facing new challenges. We will be living in significantly denser social groups, for instance. Policy decisions will be made for the good of the entire group, and it is believed by those making these plans and decisions that the populations as a whole will be best served if everyone toes the line.

Toe the line. Follow the rules. Do what you are supposed to do. If you screw up, it goes on your permanent record. Very permanent. People can check your score. Employers, landlords, parents of the person you want to marry. Continue reading

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The Complete Digital Transformation Checklist – Is Your Company Up to Speed? (Part 2)

Welcome back to our complete digital transformation checklist. Last time we covered the importance of starting with a website including a live chat feature, the inevitability of a mobile app, and why every modern company can and should have a CMS. We ended the article by promising more acronyms and as we hate to disappoint, let’s start today with the EMS.

4) Industry-Specific EMS – Enterprise Management Software

The term EMS stands for enterprise management software and this acronym is, in fact, incredibly vague. The kind of software you need to run your business depends on your industry and size but believe us, at this point there is a fast and capable EMS for almost every industry on the planet from field services to finance management. Look into software built specifically for your industry and consider streamlining the vast majority of your procedures. EMS’s can offer inventory tracking solutions, connect to your CRM for improved customer relations across the board, and are usually built to address concerns unique to the industry like specific safety inspections, appointment scheduling, and so on.

5) VOIP – Internet Phones for Everyone

If you are still paying a telco company for wired office phones and costly cell phone plans, it’s time to join the rest of the online community in internet-based phone services instead. VOIP has come a long way since Skype for individual users introduced the population at large to the idea in the first place. There are now VOIP companies that cater exclusively to businesses and call centers and the flexibility is amazing. Not only can you scale a VOIP plan to any size of team or company, you can also access numbers from anywhere including mobile devices simply by logging into an online platform.

6) AI-Assisted Data Analysis

Data analysis, once one of the most tedious chores of any sales, research, or IT team, can now be handled almost 100% by self-learning computer programs. The power of large-scale data analysis and AI intuition can cut the time you spend on data analysis down to a fraction while multiplying the available results data your teams have to work with. The fact of the matter is that computers are both better and faster at skimming data and drawing trend charts.

7) IoT Devices and Sensors

IoT (Internet of Things) is the latest craze in business technology and it looks like it’s here to stay. The concept behind IoT devices is simply that they are wifi-enabled and can be controlled from a Smart Home hub or a mobile device from anywhere in range of the wifi network. Businesses are using IoT security cameras for wireless access to their security footage. IoT lights that can be remotely switched off and a programmable IoT thermostat can work together to significantly reduce your power bills. Plus, employees are delighted by almost all IoT gadgets like, say, an IoT coffee pot that can start brewing before anyone physically gets to the break room. Continue reading