ACM CareerNews for Tuesday, October 23, 2018
ACM CareerNews is intended as an objective career news digest for busy IT professionals. Views expressed are not necessarily those of ACM. To send comments, please write to firstname.lastname@example.org
Volume 14, Issue 20, October 23, 2018
As organizations continue to embrace digital transformation projects, this is leading to new thinking about which IT skills are most valuable for advancing a career. Since one of the goals of digital transformation is to streamline IT processes, many previously critical IT skills are now becoming obsolete. It is more important to have a balanced career architecture that does not depend purely on in-depth knowledge of technologies, which are rapidly changing all the time. For IT professionals to keep moving upward in the industry, technology skills alone may not be enough. Instead, tech knowledge should act as the foundation of their career architecture, while they also develop a combination of business expertise and acumen.
Given the massive proliferation of data, business intelligence and analytics are now paramount as the foundation of any tech career. The question is how to interpret and use that data productively in a business. This information can easily be used to improve delivery of services and experiences to customers, but the difficulty is the manner in which to execute that mission. Many businesses are looking for somebody who knows how to interpret and optimize online habits of consumers, so the company can appeal to their audience in a way that will make them want to conduct their business at that organization. Machine learning is the next wave of business intelligence and analytics, and the people that are able to be conversant with that sometimes have a data science background, and sometimes have a programming background with a lot of statistical understanding.
Within the tech sector, hiring contract workers is becoming so common these independent workers will likely outnumber non-freelancers in the U.S. by 2027, if current projections remain accurate. Given the continuing rise in the number of available contract workers, it is no surprise the tech industry is looking to utilize this talent group as a solution to the ongoing tech talent shortage in the U.S. Hiring contractors results in a faster hiring process, less red tape, and an immediate solution to an urgent hiring need. As more companies are reevaluating their hiring processes to include contract workers, certain skills, such as skills related to artificial intelligence, are becoming even more sought after by top companies.
From supply chain management to marketing and sales enablement, the uses of AI are constantly expanding. Demand for AI skills has more than doubled over the last three years, according to a recent Indeed report, as more use cases and business applications have been developed. Machine learning (ML) and deep learning, subsets of AI, are also on the rise as companies are looking to do more with the vast stores of data they are collecting. Rather than replacing humans, AI augmentation will be the key to continued success among enterprises. Augmenting human intelligence with the capabilities AI provides will produce more efficient internal processes, more effective marketing campaigns and a variety of other business benefits. As a result, innovative companies today are actively looking to hire contractors for this in-demand skill set.
What Are the Fundamental Soft Skills You Need to Succeed in Data Science?
Silicon Republic, October 16
If you want your data science career to move beyond the intermediate stage, soft skills are a must. This is because data science is more than just a summation of skills or certifications. There are externalities that impact both the inputs and outputs of data science. Without soft skills, you can produce insights from data science, but they might have limited value to the business. With that in mind, say career experts, two of the most important soft skills are communication skills and general business acumen.
There are three main components of communication skills. The first is message creation. How well can you summarize the information you need to communicate into a few high-level points? What are your primary communication objectives for any given interaction? Most people do not communicate effectively because they do not start the conversation, email or presentation with any communication objectives. Without objectives, you do not really have a chance of being successful. For a data scientist, message creation is especially important. There is so much we can say about a project or approach. The second component is message discipline. Once you have chosen a message, how well do you stick to your communication objectives? It is easy to get off track or derailed by a question. Message discipline is the ability to avoid those rabbit holes and stay on point. Finally, there is message retention. The point of communication is to deliver your message. Your target audience retaining that message is a critical success factor.
The 15 Most In-Demand Blockchain Jobs
Tech Republic, October 19
Open blockchain jobs in the US surged 300% this year compared to last, according to a new report from job search site Glassdoor. As of August 2018, some 1,775 unique blockchain-related jobs were open in the U.S., compared to 446 one year earlier. The rise in open jobs has continued, even with the volatile cryptocurrency market and the fact that the technology remains in its infancy, the report found. This suggests that blockchain employers remain confident in market opportunity and are continuing to make long-term investments in these teams. As a result, the blockchain job market appears ready to continue its rapid growth into the near future.
Blockchain jobs pay well above the U.S. median salary, the report found. For example, open blockchain-related jobs on Glassdoor will net you a median base salary of $84,884 per year. Due to the diverse mixture of jobs available, salaries range from $36,046 per year up to $223,667 per year, the report found. The higher salaries are often due to the location and nature of the jobs. These higher-paid positions are often based in New York City or San Francisco, and require skills in software engineering and other in-demand technical areas, the report found. Today, the most in-demand blockchain roles employers are primarily technical and engineering roles. These roles account for 55% of all job openings in the area.
How to Keep Your Best Employees From Burning Out
Inc.com, October 18
Within any organization, there are four major personality types (Upholders, Obligers, Questioners and Rebels), and it is important for managers to recognize how each of these personalities can best be motivated to perform at their highest levels. The one personality type most likely to burn out is the Obliger, which is the person who thrives on meeting the expectations of others, even when it means taking on too many assignments or projects at the same time. These personality types are determined by the way people respond to inner and outer expectations, and how these personality types might view common workplace situations.
Obligers are the most common personality type in the world. In fact, the odds are you probably have a few of them on your team or in your organization. Because they are great at keeping up with expectations of them, Obligers often make great partners, teammates, and employees. But while there are many benefits to Obliger employees, there is also a heightened risk that they will burn out from continually accepting new projects and tasks even when they do not want to do them. If this goes on for too long, it could lead to something known as Obliger rebellion, which happens when an Obliger feels disrespected or unheard, and their defense mechanism is to shun a co-worker or quit their job. As a manager, then, you need to make sure you are always aware of how your Obliger employees are doing.
6 Reasons Why More Millennials Are Switching to Tech Careers
TechGenix.com, October 11
An increasing number of millennials are giving up their current careers to enter the technology sector. This is due to several reasons, such as the growing number and scope of available jobs. In addition, there are new options to broaden their skill sets, and opportunities to earn more while participating in intellectually rewarding work. The Bureau of Labor Statistics is predicting a 12% growth in computer and information technology jobs during the period 2014 to 2024. This growth rate is ahead of that of all other occupations for the same period. New technologies are playing a role in reinventing technical processes, and that is the leading to the creation of tens of thousands of hybrid technical roles at industrial companies.
For millennials considering a plunge into tech careers, the current situation is better than things have ever been. This is because the industry is facing a huge crunch of qualified personnel and most job seekers who are competing for the current positions are those making a career shift. Therefore, the competition is manageable. According to data analytics experts, the technology job market is growing rapidly. The dearth of qualified talent is affecting business. Employers are flocking to universities in the hope of finding candidates who can be trained to do specialized tech jobs. The goal, of course, is to hire trained professionals who can be put on the job right away. Right now, the demand outweighs the supply, and this trend is expected to hold for the foreseeable future as well.
The Pros And Cons Of Algorithms In Recruitment
Forbes, October 19
Online recruitment tools that use AI algorithms are now coming under criticism for being biased against certain types of job candidates. Silicon Valley companies and other tech giants are finding that there are more challenges in the use of artificial intelligence than originally supposed, especially when it comes to recruiting top talent. At Amazon, for example, the team had been building computer programs since 2014 to review applicant CVs with the aim of mechanizing the search for top talent. The experimental hiring tool used AI to give job candidates scores ranging from one to five stars. But by 2015, the company realized its new system was not rating candidates for software developer jobs and other technical posts in a gender-neutral way.
Despite some problems with inherent algorithmic bias, AI can still inform better, faster and smarter hiring decisions when applied selectively. However, it is imperative that AI be used to inform hiring decisions, not make them. According to recruiting experts, women already faced enough barriers in the recruitment process without technology making the situation worse. Unfortunately, as machines become more advanced and forms of AI (such as machine learning) take on a greater importance, examples of these prejudices have become increasingly commonplace. In the case of Amazon, the recruitment tool was largely trained using data from male job applications, likely due to an unconscious bias on the part of male-dominated design and development teams. In short, the AI tool was simply automating bias, rather than getting rid of it.
Why AI Still Is Not Ready to Take Your Job
IT Pro Portal, October 19
Despite the growing concern that AI-powered bots and software are about to take over jobs, the evidence in many industries is that AI still cannot make the right recommendations or perform that same types of nuanced analysis that humans can. In sectors like healthcare and hospitality, AI is still very much in its infancy. And when it comes to delivering customer service, AI also has been plagued by a number of high-profile fails. With that in mind, hiring experts are taking a closer look at which jobs and which industries are really being threatened by artificial intelligence. It might just be the case that the fear of AI-fueled job losses has been overhyped.
Healthcare IT is one area to see the failings of AI. AI is going everywhere, and even doctors are feeling threatened by the new technology. For example, it is now being used by hospitals to help with oncology, clinical trial matching and genomics. However, the AI has not yet lived up to the claims. It was reported earlier this year, following some leaked documents, that one such AI supercomputer had been poorly trained to assist with cancer diagnosis. The program failed to perform its basic function, instead making several incorrect and unsafe recommendations. In fact, it was suggested that the program is not usable in most cases. In this example, then, even the best medical AI was still unable to perceive and understand things the same way a human can. Plus, being a good doctor is not just about diagnosis and treatment. There is a distinct need for the more human traits that enable a good, reassuring bedside manner, something AI is not likely to achieve soon.
Changing Who Pays For CS Professional Development in the United States
Blog @ CACM, October 17
The model of who pays for CS professional development continues to change, and that is forcing both educators and local school district administrators to re-think their priorities. In 2012, for example, most CS teacher professional development was paid for by the National Science Foundation or Google and was delivered from local universities. That all changed in 2013, when the Code.org movement began. This movement soon grew into an organization that created and provided curriculum, offered teacher professional development, and worked with states and districts around public policy initiatives. A recent report from Code.org showed that 44 states have enacted public policies to promote computing education in the five years from 2013 to 2018, and much of that happened through the influence of Code.org, which famously paid for all CS teacher professional development. So what happens if Code.org scales back funding?
The completely free CS teacher professional development from Code.org meant that districts did not have to gamble their scarce funding on teaching computer science, when they did not know that it would be worthwhile. Would these CS courses become important in the district and in the state? Would parents want this? Would students take the courses? But it is also a problem when Code.org bears all the risk. The districts bear no responsibility. They have no ownership. Education in the United States is locally controlled, and decisions are decentralized. If Code.org (or NSF or Google) are paying for all the development of CS teachers, then the districts may not get to implement what is really important for their local community.
Openness in Education
eLearn Magazine, September 2018
In a wide-ranging interview, Dr. Martin Weller, Professor of Educational Technology at the Open University (UK) and the president of The Association for Learning Technology (ALT), offers his thoughts on openness in education and how the movement has evolved over the past five years. Weller has been a prominent figure in the movement for opening up education and has published many articles and four books on topics related to open and online education. As Weller explains, openness has moved from being a peripheral, specialist interest to a mainstream approach, especially with the popularity and spread of different dimensions of open practice (e.g. open access resources and publishing, massive open online courses, and open scholarship). In short, says Weller, the application of open approaches in all aspects of higher education practice has finally gained legitimacy.
Since 2014, openness in education has largely seen a pattern of steady adoption. While openness is now mainstream, that does not mean that every academic is now involved in the open movement. Rather, it means that open approaches are now viewed as legitimate. We have seen a steady growth in open textbooks, expanding models of open access publishing, and continued engagement with MOOCs. None of these have suddenly transformed higher education over the past several years, but they have all continued to grow steadily. So the various aspects of open education can be seen as components in a toolkit that are used as needed. For instance, some institutions want to reach a specific group of learners, so they might use a MOOC, while others want to focus on flexibility so they might adopt open approaches to course production.
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