Author Archives: Jeff Landine and John Stewart

The Role of Varying Motivations to Counsel

Posted by: Jeff Landine and John Stewart on April 28, 2020 12:55 pm

The impetus for this series of blogs comes, for the most part, from conversations we have had with recent Counselling Program graduates and from our efforts to assist past graduates in the later stages of their careers as they try to navigate the rapidly changing landscape of counsellor regulation. In the interest of transparency, the majority of graduates we know who see counselling as a work role for implementation later in their career, already have a career path established as teachers, nurses, social workers, etc. The majority of students who graduate from our Counselling Program and others that we are familiar with, seek work in a counselling role immediately or go on to pursue more education. It is the small, but perplexing, group of graduates who complete the degree, and then put the counselling role on hold, that we want to consider for this series of blogs. We want to discuss a number of motivations people have for choosing counselling as a profession and to determine if, within these motivations, societal change enables, even demands, continuing work after people retire from other professions to practice counselling therapy.

Most, if not all counsellors, have entered this line of work because they want to help create positive change in the lives of others. But people are able to do that in the relationships they already have in their lives or by volunteering, neither of which requires extensive education and supervised experience, not to mention the expenditure of time and money. It wasn’t too long ago, in fact, that a significant amount of counselling was provided in lay-counsellor roles. The early 20th century saw the emergence of an increased emphasis on the value of all human beings and, coupled with the changes brought on the Industrial Revolution, the need for mental and emotional support increased. The medical community (including psychiatrists and psychologists) were managing the more difficult cases but many people didn’t require that level of service to function normally. So well-intentioned and caring members of public and church communities volunteered to provide a listening ear to those in their community who needed it. Students in the public school system learned who the teacher was in their school that they could go talk to when they had a problem. Pastors provided counselling services to their congregations. Counselling as a profession has grown in the context of historical events such as the Industrial Revolution, the Great Depression and world conflicts. Counselling started becoming professionalized in the 1950s and as a result, it is now possible to combine the motivation to help people with other motivations for becoming a counsellor. The question that persists, like a mosquito in a dark tent, is why individuals are waiting until one professional practice ends to start taking the necessary steps to engage in professional counselling? Perhaps it is a growing awareness of the need for a counselling therapist in their interpersonal sphere. For example, school teachers, social workers and nurses all experience clients who need additional interventions that furthering their educational and professional training enables them to provide.

We have heard a good number of secondary reasons for making the decision to complete the Counselling program that we work in. We have had people apply who are working in other non-helping professions who are seeking more meaningful work. Others are looking for flexibility in their career. For those applicants coming from the school system, many have a desire to keep learning and pushing themselves forward and counselling is the most interesting option. Unlike many other graduate programs, Counselling is typically found in Faculties of Education, which bring opportunities for part-time completion, flexible class scheduling and online course options. For someone looking to increase their education (and pay), these programs are particularly attractive because they don’t require the applicant to quit their current job. Finally, counselling is a profession where life experience is valued, so we often get applicants from people looking for a second career.

There are many viable reasons for starting down the path towards becoming a counsellor and it is not our intention to judge the motivations of people who have considered and are considering counselling as a profession. Social desirability often masks the motivations people have anyways. The decision to “sideline” the counselling role until later in one’s career, however, has ramifications for the individual, counsellor education programs, regulatory bodies and the profession. We will discuss these ramifications in more detail in the next blog.

*The views expressed by our authors are personal opinions and do not necessarily reflect the views of the CCPA

Nonconformity in Choosing Counselling as a Career

Posted by: Jeff Landine and John Stewart on January 9, 2020 2:02 pm

Typically blogs about career counselling address issues that relate to the delivery of career counselling, for example, the impact of Artificial Intelligence on future jobs and the need to prepare clients for that eventuality.  For the next few entries, however, we are going to shift our attention to the diverse perceptions that exist on the counselling profession and consider motivations to engage in counselling as a career.

We have, combined, over 50 years’ experience working as counsellor educators at the university level and have both been involved, throughout our careers, with national, provincial and local associations whose mandates are to further the profession of counselling. In these roles we have seen countless students through the process of preparation for a career in counselling and have first-hand experience in the processes of legitimizing these students’ positions as professionals by working with certification and licensing boards and committees.

Despite the recent increase in credentialing and professionalization of the counselling role, one constant we have seen is the frequent consideration by these students of their counselling education as preparation for a professional role somewhere down the road. On more than one occasion, I have heard counsellors-in-training refer to their intentions to have this graduate degree in their “back pocket” for use later in life, either when they no longer want to continue with their present work or as a transition into retirement and as a pension supplement. This approach to counselling as a career is surprising, as we don’t see the same approach employed in other professions. Nobody we know gets their Red Seal as a plumber so that they can open a side business in retirement. We don’t know of any B.Ed. graduates who choose not to teach after graduating, deciding instead to wait until later in their career to join the ranks of school teachers. This phenomenon begs the questions, “Why does counselling, more so than other professions, lend itself to be a career of convenience/second thought?” While people might pursue a law degree, for example, without the intention of practicing as a lawyer, the dynamic we are questioning is whether interest in the subject (in this case counselling) will be used as a support in the work being done or not. John completed a vocational Master of Theological Studies degree out of interest (during the latter parts of his career as a professor), with no intention to be employed as a pastor. Unlike these examples, counselling students appear to be intentional in using the counselling preparation they receive for employment purposes later in their career or after having retired from another job.

The history of counselling as a formal profession starts with the emergence of vocational counselling in the late 19th and early 20th centuries (Shepard & Mani, 2014).  The advent of large cities, built around manufacturing and industrialization, created the need for vocational guidance; however, the influx of people to these urban centers resulted in increases in unemployment, poverty, poor working and living conditions and crime. Corresponding to the increase in social problems, support systems typically declined as people moved away from their families and home communities. The development of counselling as a profession in Canada over the ensuing century was largely driven by a vocational focus but the resulting profession has adapted itself to the connection between career and personal difficulties and the increasing need for mental health support. Counselling and psychotherapy now make use of psychological theory and concepts and counsellors today are much better prepared to work with psychopathology in their clients.

In the next few blog entries we will explore the nature of Counselling education, credentialing and employment in an effort to decipher the motivations and career planning that have, in many instances, relegated counselling to a “sideline” or back-up profession.

Shepard, B., & Mani, P. (2014). Career development practice in Canada. Toronto, ON: CERIC Canadian Education and Research Institute for Counselling.

*The views expressed by our authors are personal opinions and do not necessarily reflect the views of the CCPA

Reflections of the Future of AI Technology and its Implementation

Posted by: Jeff Landine and John Stewart on October 25, 2019 2:26 pm

In our last three blogs, we provided a brief overview of the field of Artificial Intelligence and its impact on the world of work along with suggestions to help career counsellors respond to these innovations with their clients.  While predictions suggest a massive immediate impact on the workforce, in this blog, we will discuss some issues that we think need to be addressed before implementation and that may even delay the use of some deep learning technology.

Predictions are that within five years, deep learning machines with the ability to mimic human cognitive functions will take over many thousands of jobs (1). Currently, these new innovations are being used in law enforcement, health care, scientific research and even determining what information we see on Facebook.  Before these deep learning machines are deployed, there are several social policy and legal issues that need to be clarified (2). One issue focuses on the lack of transparency in the development of algorithms (3). Due to the layering of deep learning algorithms, as the machine processes larger volumes of data, the algorithms make connections between layers that help to make more refined decisions. Some developers have voiced concerns over whether the decisions made by these machines can be trusted due to the changes in the algorithms.

This issue of trust raises legal issues that have yet to be resolved by the courts (4). For example, if these machines make biased decisions resulting in a human rights discrimination against a candidate for not being short-listed for a job, the issue of who is responsible is raised. Is it the developer, the owner of the machines, or the machines? We suggest that before implementing such technology, policies and legal statutes need to be in place. For example, “can a machine be a legal entity much like a corporation?” Or, “what standards of security need to be demonstrated by the machines to ensure user privacy of information before they are deployed?” Such decisions and policies will help to prevent unnecessary legal disputes.

Additionally, there are indicators to suggest the public is already leery about robotic-made decisions, and we think this attitude will have a negative impact on bringing newer innovations online until testing demonstrates no biases or weaknesses in deploying them. For example, autonomous cars have been in the media for over a decade. Current research suggests that 94 % of US citizens know about these cars; however, 56% of them indicated they are not ready to ride in such vehicles citing a lack of confidence and trust in robotic decision-making and a mistrust in the general safety of the technology (5).  To change these attitudes, industry has more development and promotional work to do before the public will use this technology.

With smart machines, there is the possibility of collecting large amounts of personal data from users that could be used for nefarious purposes.  For example, one has only to look to Facebook as a social media platform and how foreign agents were able to use it to influence voters in the 2016 US federal election. There was a public outcry concerning the use of information obtained by Cambridge Analytica from millions of Facebook users by political parties to build US voter profiles (6).  At this point, policies are in short supply to protect consumer information and to regulate accountability should breaches be made. With the use of deep learning machines and the possibility of personal data being collected, safeguards are needed to ensure confidentiality and protection.

Career counsellors can play a significant role in dealing with these concerns. They can be advocates for their clients by working on policy development committees concerning the deployment of smart machines in the economy. Career counsellors have ethical guidelines, which regulate the use and storage of their clients’ personal information. These guidelines would help in developing policies around the storage, use and dissemination of information collected by deep learning machines. Career counsellors, through their professional associations, can send briefs to major banks, food retail companies, insurance companies, medical corporations, professional associations, and politicians to express their concerns over the lack of parameters surrounding the use of deep learning machines.  We think these endeavors will help to raise public awareness and develop policies and laws before deep learning machines become.

By Jeff Landine and John Stewart

Sources Used
  1. AI, automation, and the future of work: Ten things to solve for (June 2018). Retrieved on August 26, 2019 at
  2. Artificial intelligence and machine learning: Policy paper. Retrieved on August 1, 2019 at
  3. Gershgorn, D. (2017) AI is now so complex its creators can’t trust why it makes decisions. Retrieved on August 1, 2019 at
  4. Beauchemin, H. (2018). Key legal issues in AI. Retrieved on September 19 at
  5. Smith, A and M. Anderson. Americans’ attitudes toward driverless vehicles. Retrieved on August 1, 2019 at driverless-vehicles.
  6. Cambridge Analytica and Facebook: The scandal and the fallout so far. Retrieved on August 1, 2019 at fallout.html.

*The views expressed by our authors are personal opinions and do not necessarily reflect the views of the CCPA

Artificial General Intelligence and its Impact on Jobs

Posted by: Jeff Landine and John Stewart on July 19, 2019 10:57 am

Artificial Intelligence (AI) is typically divided into Artificial Narrow Intelligence (ANI) and Artificial General Intelligence (AGI). In our last blog, we dealt with ANI and its implications in the workplace. In this blog we will deal with AGI.

AGI focuses on developing and using deep artificial neural networks (a set of computer algorithms) to process massive amounts of data in a relatively short time. “Deep” refers to the number of layers of computer algorithms, which permit the computer to form connections between these layers. Because of these connections, computers are essentially able to program themselves after multiple trials of processing different sets of similar data. Once the accuracy and efficiency of the model is determined by humans, it becomes available to those who want competent analyses of information pertinent to operating their business and/or performing their occupation.

Predictions are that many new jobs will be created as the field of AGI develops. To illustrate these predictions, presently six different individuals are typically deployed when using deep learning methods to develop new computer models. The decision-maker secures funding and resources to complete the project. The stakeholder quantifies the business value of a proposed solution. The domain expert gets familiar with the work area and problem to be solved. The data scientist translates business problems into computer tasks. The data engineer determines possible databases to use in simulation; and a systems architect designs the infrastructure, such as servers to handle big data. Within a relatively short time, the number of individuals and specializations needed to develop computer models will increase and result in jobs with new specialized tasks.

The impact of AI on the workplace is anticipated to be swift and impactful. A report from the World Economic Form in 2018 projected that these computer programs are expected to create 133 million new jobs by 2022; however, 75 million jobs are likely be displaced. This leaves a net new jobs creation of 58 million due to growth in AI.  An RBC report suggests that Canada will add 2.4 million new jobs to the workplace in the next four years. However, it also suggests that the current generation of young people are not being prepared for these sweeping changes. Workers will need digital skills, that is, the ability to understand digital items, digital technologies and the Internet fluently.  They will also need human skills such as critical thinking, active listening, social perceptiveness, and complex problem-solving skills for job success.

Career counsellors face three immediate challenges: disseminating labour market information, counselling workers who are displaced, and helping existing workers find retraining or upskilling programs. Part of this challenge is the speed at which these predictions are coming true.  Career counsellors and their professional organizations will need to produce materials to provide clients with significant labour market information related to displacement and innovations in the workplace.  Individuals who lose their jobs often experience low self-esteem, depression, and lack of self-confidence. As well, prolonged periods of unemployment can lead to suicide ideation (Milner, Page & LaMontagne, 2013). Counsellors will need to deal with these issues before they help their clients make workforce changes. Counsellors will need upskilling themselves to understand the tasks being performed in these new jobs, and to assess their clients’ current transferable skills for the new jobs. They need knowledge of available educational programs that offer uptraining. Further, career counsellors need to be familiar with government support programs that can help their clients make workplace transitions.

Despite these dire predictions, we suggest it will be more “yellow light” than red or green. Many Canadian employers are small to midsize businesses and may not have the capital to adopt these AI technologies presently. To deal with these rapidly developing workplace needs, we think there will be local, provincial and national responses, a part of which will provide agencies with the needed help to deliver services.

Suggested Reading

A beginner’s guide to automated machine learning & AI. Retrieved May 27 at

Chowdhry, Amit. (2018). Artificial intelligence to create 58 million new jobs by 2022, says report. Retrieved May 27 at

Human intelligence and intuition critical for young people and jobs of the future. Retrieved May 27 at

Milner, A., Page, A., & LaMontagne, A. D. (2013). Long-term unemployment and suicide: a systematic review and meta-analysis. PloS one8(1), e51333.

Jeff Landine and John Stewart
Faculty of Education, University of New Brunswick, Fredericton, N.B.

*The views expressed by our authors are personal opinions and do not necessarily reflect the views of the CCPA

Artificial Narrow Intelligence and its Impact on Jobs

Posted by: Jeff Landine and John Stewart on May 24, 2019 12:43 pm

Artificial Intelligence (AI) is typically divided into Artificial Narrow Intelligence (ANI) and Artificial General Intelligence (AGI). ANI deals with machines or robots that can perform a task or function such as welding on a manufacturing assembly line. These robots/machines are designed to perform one task and are not able to adapt to other tasks unless they are programmed specifically. Conversely, AGI deals with computers that are able to perform different levels of human intelligence, such as perceiving, reasoning, problem solving, and interacting in the context with some creativity. Additionally, AGI computers can make decisions to move information between databases.  Presently, much of thinking behind AGI involves future projections based on theory and some recent innovations in deep learning, one of the main Canadian focuses in AI research. In this blog, we want to focus on ANI and its implications for jobs going forward.

The influence of ANI has already been felt in the workplace. For example, during the recessions of the 1980s and 1990s, the manufacturing industry replaced many line workers with robots. Today, there are computer programs with the abilities to do word processing, perform translations, and numerous smart phone Apps that execute many functions via the internet. These innovations are already impacting the way information is accessed and business is transacted.  Predictions are that narrow intelligence will eliminate jobs that require repetitive manual labour, and jobs characterized by standardized tasks. For example, some have forecasted that as many as 42% of all jobs in Canada are in danger of being automated. The degree to which these jobs can be automated will influence their availability in the workplace.

However, due to innovations, new jobs have been and will be created. For example, there are 845 jobs listed under the AI title on LinkedIn Canada’s website, including engineers, technologists and technicians with specific specialities in AI. Due to the structural unemployment created, workers will need to either quickly reskill in AI competencies or transition to other jobs in the workplace. Workers who seek AI jobs will need to acquire new hard skills: problem-solving and analytical thinking skills; skills that enable them to build, maintain and repair software programs and machines; and, the ability to look for technological innovations that enable businesses to remain competitive. Additionally, they need soft skills, such as competent languages skills to explain technical information, and empathy to understand the stress others experience due to work transitions.

It seems quite certain that the number of jobs characterized by repetitive tasks and requiring low cognitive skills will continue to decrease.  This decrease has several implications. Career counsellors will need to understand the scope of AI educational programs, their availability and entrance requirements. Further, counsellors will need labor market information to benefit their clients. For example, individuals, aspiring to jobs in AI and those already in the workforce will need to have had formative education in STEM subjects (Science, Technology, Engineering, Mathematics) or acquire it to complete technician and technology programs in computer design, operations, and maintenance. Those currently in school will need to master STEM courses if they intend to choose educational paths leading to careers in AI. AI specialists in the workforce will need to upgrade continually to keep up with innovations in their field. And, employers will need to develop policies that enable workers to take educational leaves regularly to master changes issuing from technological innovations.

Jeff Landine and John Stewart
Faculty of Education, University of New Brunswick, Fredericton, N.B.

Suggested Readings
Retrieved on March 20, at:
Retrieved on March 20, at:”pan-canadian-artificial-intelligence-strategy.”
Retrieved March 20, at: www.+RG-“CPA-Introduction-to-AI-What-You-Need-to-Know”-February-2019.pd.
Retrieved March 20, at:”RoboticsAI3D”Final_Web_e.pdf.
Retrieved on March 20, at:”4-ways-ai-artificial-intelligence-impact-financial-job-market.”

*The views expressed by our authors are personal opinions and do not necessarily reflect the views of the CCPA

The Impending Impact of Artificial Intelligence on the Work Force

Posted by: Jeff Landine and John Stewart on April 23, 2019 2:50 pm

Throughout our research, we have found that there is nothing more embedded into our lives than career.  As we contribute to the Counselling Connect Blog, our intention is to explicate, using a mix of research and reflective opinions, some of the dynamics that impact career. We start with a consideration of Artificial Intelligence (AI).  AI is a branch of computer science that focuses on programing computers with the ability to resemble intelligent behaviors including learning, reasoning, planning, observing and/or processing language.  We think this blog, plus several future blogs, will inform career counsellors in two ways: understanding the impact of AI on careers; and counselling clients entering the workforce, or who are displaced due to AI innovations. As a disclaimer, our expertise lies in the realm of Career Psychology and not in AI; however, we are doing a lot of reading on the subject.  In this blog, we want to examine some of the proposed advantages and disadvantages concerning the impact of AI on future job availability.

Recent advancements in AI suggest that we are in a “fourth industrial revolution,” but with significantly more implications than previous revolutions. We think there is no doubt that AI will take over some jobs due to such technological innovations as robotics, machine learning, and 3-D printing; and through the impact of AI on manufacturing, retail jobs, and in other domains such as legal and medical.  It seems that the question is not when, but how rapidly and profoundly automation will change the workplace.  Many think that AI will displace most jobs requiring manual and routine labour – machines can do it faster and with more accuracy. Further, with the advent of self-driving vehicles, many truck drivers, couriers and taxis will be displaced. Recent developments in diagnostic work using computers will impact the medical profession. Currently computers can diagnose abnormalities in x-rays with as much accuracy as radiologists.

On the positive side, AI can be an aid to workers.  Instead of fearing that robots and AI might reach a “singularity” and replace workers, “multiplicity” proposes that humans will work with machines to solve problems and develop leading-edge technology.  Automation will create new jobs not presently conceived of, just as personal computers did in the past. For example, in Human + Machine: Reimagining Work in the Age of AI, Paul Daugherty and Jim Wilson envision two categories of workers – explainers and trainers, both illustrating the idea of intelligence augmentation, that AI systems can be designed to augment human work behavior.  Explainers will help humans work with machines and trainers will develop AI systems to do workplace tasks.  For example, explainers will work in clarifying decisions made by computer algorithms and explaining them to supervisors and executives. And presently, trainers are developing chatbots that, in response to human consumers, will continue to improve on language recognition to better serve them.

In conclusion, we think that the outlook will be more favourable than bleak. Certainly, there will be job changes and job loss.  However, jobs taken over by machines will not diminish the work to be done. Quite the contrary, just as electronics and information technology created more jobs than were lost, AI will do the same.  We see several implications for career counsellors and their practice.  At the present we do not see counsellors being replaced by chatbots/robots due to the need for client empathy, something that AI has not been able to simulate yet. However, it is our opinion that the information that informs the practice will need to be upgraded on a regular basis.  Most likely, this information will be dispensed by a chatbot or other a computer programmed to process human speech. Counsellors will need some degree of understanding to help clients process the changing aspects of the skills/tasks need in some work domains such as business, management, medicine, and law.  Counsellors will need to upgrade regularly their knowledge of new jobs created from advances in AI, including their location, and the entrance requirements of educational programs and their costs leading to employment in these jobs.

Jeff Landine and John Stewart
Faculty of Education, University of New Brunswick, Fredericton, N.B.

The First Industrial Revolution used water and steam power to mechanize production. The Second used electric power to create mass production. The Third used electronics and information technology to automate production. The Fourth is fusing together technologies that are blurring the lines between the physical, digital, and biological spheres.
Suggested Readings:
Daughterty, P. R. and H. J. Wilson (2018). Human + machine: reimaging work in the age of AI. Boston, MA: Harvard Business Review Press.
Retrieved on February 13, at:
Retrieved on February 13 at:
Retrieved on February 13 at:

*The views expressed by our authors are personal opinions and do not necessarily reflect the views of the CCPA