How Safe Is My Job

How Safe Is My Job is the product line of Educaship Alliance LLC that includes:

1. 15-minute educational video published at Educaship YouTube Channel and video-sharing resources of CNM Cloud.
2. HowSafeIsMyJob.com website.
3. Paid appointment that consists of individual assessment of the AI impact on customer's job, as well as one-on-one assistance in strategy development and execution.
4. Article published at readable content resources of CNM Cloud. This very wikipage serves as its draft.

AI is best at

#AI's combined #Computing power and #Scalable persistent memory already exponentially exceed similar capacities of humankind combined. #AI systems already beat human champions in games like Go, Doom, and Warcraft. No human can memorize as many books as #AI can, no human can program as many lines of code as #AI can, and etc.

There are several functions at which #AI systems are the best.

Dangerous task execution

AI-driven, AI-powered, AI-controlled drone, robots, rovers, and vehicles can perform those tasks that normally involve risks to human lives such as exposure to:

• Dangerous situations such as (a) combat and defense operations, (b) crime and violence, (c) defusing explosive devices, (d) fire fighting, (e) health emergencies and infectious diseases, (f) natural disasters such as earthquakes, floods, hurricanes, tornadoes, and wildfires, (g) operations in remote or challenging locations, high-rise or underground sites, and conflict-prone or hostile areas, as well as (h) water-related dangers.
• Hazardous environments such as (a) agricultural pesticides and large animals, (b) electrical hazards, (c) environmental hazards including air pollution and chemical spills, (d) flammable and toxic chemical and substances, (e) confined spaces, such as silos, tanks, and tunnels because of risks of asphyxiation, toxic gas exposure, and difficulty in rescue operations, (e) deep sea or underwater, (f) nuclear power plants, (g) outer space, and (h) workplace hazards such as chemical exposure, flammable and volatile materials, high temperature, and/or noise pollution.

Both #AI and humans can conduct inspections, perform maintenance, and undertake projects in dangerous situations and hazardous environments. However, reduction in risks to human lives has also economic reasoning. Manufacturing a robot and its AI training is way cheaper than giving birth, raising, and professional training of a human specialist.

Knowledge logistics

#AI systems are the best to capture, organize, store, and retrieve knowledge to make it available 24/7. No human can match (a) the accuracy and precision, (b) depth of insights, (c) magnitude of information, and (d) speed with which AI processes knowledge.

While #AI is superior in knowledge operations and logistics, it's important to note that it is most effective when working in collaboration with human expertise. Human creativity, ethical considerations, and judgment are elements that #AI lacks, and the combination of #AI and human capabilities often results in more comprehensive and well-rounded solutions.

Modeling and simulation

#AI systems are the best to accelerate:

• Experimental cycles in science to speed up advancements.
• Mocking up digital products such as document drafts, software applications, and websites. In that way, human contributions may switch to replacement of usefully wrong parts with right ones, while reducing the time and cost of development.
• Prototyping physical products in construction and manufacturing. This reduces the time and cost of physical prototyping, enabling faster and more efficient product development.
• Recreating personal medical conditions, treatment outcomes, and surgical procedures in healthcare.
• Replicating real-world environments to provide a lifelike and immersive experience for learners. This can involve mimicking scenarios, situations, or tasks that learners might encounter in the actual environment they are preparing for.

Both humans and #AI can model and conduct simulations. The speed is the difference. For instance, an #AI system can draft hundreds of birthday letters before an individual writes one. An #AI system can also draft millions of construction projects before a human architect completes one.

Pattern recognition

#Discriminative AI are the best in #Pattern recognition. Those #AI systems normally analyze their data in order to be utilized in:

• Consistency and anomaly identification. #Discriminative AI may check one's grammar and syntax, detect activities and objects, notice trends, perform business intelligence, as well as offer valuable insights for informed decision-making.
• Predictive analytics to analyze historical data and make predictions about future trends that can be used in finance, healthcare, and manufacturing for forecasting and planning.

Both humans and #AI can notice and recognize patterns. However, a human brain is limited with regards to the volume of data it can process. Humans also acquire biases and preferences such as selective attention. Only #AI can process that much that complicated data that fast to find its anomalies, consistencies, patterns, and trends.

Repetitive task automation

#AI systems are the best to automate repetitive tasks. They can enhance efficiency, reduce human workload, and improve the accuracy and consistency of repetitive tasks in various industries. Automation of:

• Intangible tasks at which #AI is superior with regards to productivity include (a) content moderation, (b) customer support and help desks, (c) data entry and processing, (d) financial transactions, (e) human resource retention and recruitment support, (f) IT operations and maintenance, (h) language translation, (i) social media management, (j) any office-type work such as document and email sorting and filtering.
• Tangible tasks at which #AI is superior with regards to productivity include (a) agriculture and, especially, precision agriculture, (b) cleaning and waste management, (c) construction and demolition, (d) healthcare routine, (e) infrastructure maintenance, (f) manufacturing and assembly, (g) security and surveillance, (i) shopping and retail, (j) transportation, warehouse and logistics, as well as (k) all the tasks in environments that are dangerous to human beings such as deep sea, fire, mining, and outer space operations.

Without #AI, humans can automate repetitive tasks through step-by-step instructions and strictly programmed devices such as numerically controlled machines. However, each deviation in those tasks requires costly changes such as machine re-programming or instruction amendments.

On the contrary, autonomous systems such as self-driving cars, drones, and robots can perform tasks without that costly and time consuming human intervention.

Scalable personalization

#AI systems are the best to personalize at scale. #AI systems excel at swiftly tailoring content or features to align with specific purposes, contexts, and individual preferences. In the realm of language, this adaptation encompasses:

• Transforming the content while adjusting its overall style, catering to the target user's age, changing its tone or size, emulating the style of a famous person, extracting and summarizing relevant information, and translating into different languages among other factors.
• Delivering the content to meet the unique requirements of individual users. #AI systems can deliver the contents (a) promptly, (b) in various formats such as images, spoken narration, specific voices, text, or video, and (c) through the preferred media channel of each individual customer.

Both humans and #AI can personalize products to a particular customer. However, only #AI can do so at massive scale. At very least, no human can speak in as many languages as #AI can.

AI impact on jobs

The impact of #AI on jobs is a complex and evolving topic.

Jobs AI creates

Obviously, #AI creates new jobs and industries. This very crash course wouldn't make that sense, let say, in a year of 2000 as it does today.

1. AI development creates demands in (a) AI copywriters and content creators, (b) developers of AI applications, virtual reality (VR) and augmented reality (AR), (c) engineers, (d) ethical AI specialists, as well as (e) AI model and ML trainers.
2. AI integration creates demands in (a) AI system integrators, (b) customer experience designers, and (c) human-machine teaming specialists.
3. AI operations creates demands in (a) AI analysts and strategists, (b) AI educators and trainers, (c) AI intervention supervisors, as well as (d) AI-tool operators.
4. AI maintenance creates demands in (a) autonomous drone, robot, rover, and vehicle technicians, as well as (b) AI hardware specialists.
5. AI regulation creates demands in (a) AI compliance managers, (b) AI governance and policy analysts, and (c) AI reinforcement officers. As #AI becomes more integrated into various aspects of society, there is a growing need for bias, ethical, privacy, and security considerations and, therefore, regulations. Professionals will likely be required to understand the implications of #AI on societal impacts, promoting responsible and ethical AI development and use.
6. Dangerous zone exploration such as explorations in deep sea, high-rise, outer space, and underground zones may create demands in (a) exploration supervisors and (b) new area development strategists.
7. Remote waste management may create demands in (a) remote waste supervisors and (b) utilization optimization strategists.

In the meanwhile, the landscape of AI-related jobs is dynamic. The integration of AI into various industries will likely lead to the creation of new and diverse roles as technology continues to evolve.

Jobs AI replaces

Most likely, due to #Repetitive task automation, by 2050, #AI systems will automate or significantly augment the overwhelming majority of jobs composed of repetitive and routine tasks, as well as replace #Dangerous task execution.

• AI-powered assistants already affect jobs of (a) accountants and bookkeepers, (b) cashiers, (c) data entry clerks, (d) file clerks, (e) IT support workers, (f) routine inspectors and testers, (g) security and fraud detectors, (h) software coders and programmers, and (i) translators and interpreters.
• AI-powered chatbots already affect jobs of (a) call center operators, (b) customer service representatives, (c) paralegals, (d) telemarketers, (e) human resource generalists, as well as (f) insurance and loan underwriters.
• AI-powered drones are affecting jobs of (a) aerial inspectors, monitors, security guards, and surveyors, (b) remote couriers and delivery drivers, (c) search and rescue teams, and (d) wildlife conservationists.
• AI-powered robots equipped with IoT devices, sensors, and manipulators already affect jobs in routine (a) agriculture, (b) assembly, (c) food production and service, (d) healthcare, (e) hospitality, (f) manufacturing, and (g) retail, as well as general laborer and low-wage jobs across all the industries.
• AI-powered vehicles and rovers already affect jobs of (a) drivers, (b) forklift operators, and (c) logistics and warehouse workers.

In other words, three categories of workers tend to be more susceptible to competition with #AI: (1) workers who strictly follow their step-by-step instructions, (2) workers who process data, natural languages, and software codes, as well as (3) those who risk their health or even life while performing their duties. Additionally, the advancement of technology and AI may impact job roles in ways that are not entirely predictable.

Jobs AI transforms

Development of #AI systems produces #Jobs AI creates. #Intelligent machines can possibly do routine, repetitive tasks more efficiently and at lower costs, which may result in #Jobs AI replaces. Simultaneously, #AI systems have the potential to transform or, at least, significantly impact those jobs that are going to stay.

AI tools will improve the efficiency of employees involved in unique and non-repetitive tasks. As a result, employers may evaluate whether to decrease the workforce or assign more tasks to sustain productivity. This evaluation may lead to either downsizing or expanding job roles. The last change will result in #Dynamics of transforming jobs.

Those tasks that are going to be evaluated include:

• Creative production. #AI will augment creative production by offering data-driven insights and collaborating with human creatives to enhance ideation and design processes.
• Decision making. #AI will revolutionize decision-making by processing vast datasets rapidly, providing predictive analytics, and offering insights to facilitate more informed, data-driven choices across various industries.
• Knowledge work. #AI will transform knowledge work by facilitating data analysis and augmenting human decision-making, ultimately enhancing efficiency and productivity in information-intensive professions.
• Project management. #AI will revolutionize project management by optimizing resource allocation, predicting risks, and enabling more efficient planning and execution of projects.
• Research, science, and innovation. #AI will revolutionize research, science, and innovation by accelerating data analysis, facilitating complex simulations, and uncovering patterns, thereby expediting discoveries and pushing the boundaries of knowledge.

In other words, jobs that require human traits like empathy, authentic creativity, and complex problem-solving are likely to remain in demand. However, those workers who are equipped with #AI skills, are generally more competitive than those without such skills due to the powerful capabilities of #AI.

Dynamics of transforming jobs

Because of #AI impact on jobs, there will be #Jobs AI creates, #Jobs AI replaces, and #Jobs AI transforms. The transformation of jobs will affect how work is organized, the skills and competencies required, and the overall employment landscape. Several key elements contribute to the dynamics of transforming jobs.

Diversification of tasks

Within #Jobs AI transforms, employees may be given a wider range of duties that align with their skills and competencies, allowing them to (a) deepen and/or personalize existing services such as customer support, education, human resources, legal services, and social work, (b) supervising #AI systems, (c) planning for new powered by AI functions, and (d) making decisions on optimization of existing organizational resources.

Today's roles	Diversified tasks
Teachers and educators	Education optimization strategists and personalized learning facilitators.
Human resources (HR) professionals	Company culture nurturers, employee developers, and strategic workforce planners.
Marketing and advertising professionals	Marketing optimization strategists, campaign strategists, and creative aspects director.
Financial analysts	Financial strategists, risk managers, and stakeholder relationship managers.
Creatives (designers, writers)	Creative production strategists.
Manufacturing workers	Automated production supervisors and production optimization strategists.
Cybersecurity experts	Cybersecurity strategic planners and novel threat handlers.
Customer service representatives	Customer issue handlers, emotional intelligence officers, and building customer relationships.
Legal professionals	Client integrationists, complex legal analysts, and legal strategists.
Logistics and supply chain professionals	Automated logistics supervisors and supply chain optimization strategists.

Dynamics in needs for labor

#AI reshapes the composition of #Knowledge, skills, and abilities (#KSAs) that are highly valued in the workforce. That development prompts several dynamics such as:

1. Knowledge devaluation. #Assistants and chatbots, as well as #Expert systems are going to degrade the value of worker knowledge. Factual and/or theoretical information of human personnel over time will become less valuable than the data backed by #Persistent scalable memory.
2. Rise in unstructured tasks. AI's proficiency in executing routine and repetitive tasks enables humans to dedicate their attention to more intricate, unstructured, and strategic activities. Workers may find themselves collaborating across different disciplines and functions to unlock the full potential of AI technologies. This transition encourages a more interdisciplinary approach to work, cultivating a broader understanding of various domains.
3. Uniquely-human skill appreciation. The spread of #AI is spreading demand for higher-level, uniquely human tasks such as authentic creativity, critical thinking, emotional intelligence, innovation initiative, problem-solving, and unstructured decision making that non-#AGI machines lack.
4. Sharp demand for AI skills. The rise of #AI shall boost those skills that complement and enhance automated processes. AI skills are the abilities and competencies that individuals possess to effectively work alongside, leverage, and contribute to artificial intelligence systems. AI skills may include understanding AI concepts, data literacy, programming proficiency, problem-solving in a data-driven environment, and the capacity to collaborate with AI technologies to optimize outcomes.

Shifts in training focuses

Because of #Dynamics in needs for labor, #AI is changing the workplace demand for workforce competencies. So, the supply shall change:

1. Decline in formal instruction is prompted by the rise of #AI, requiring a reassessment of training programs. Conventional educational frameworks may have to undergo adjustments to prioritize skills that are less prone to automation. This entails nurturing adaptability, fostering a commitment to just-in-time learning, and developing the capability to engage with evolving technologies.
2. Increase of on-demand just-in-time training. In the face of rapid technological evolution, the significance of on-demand training grows. To stay abreast of the dynamic job market requirements, workers might find it essential to refresh their existing skills or acquire new ones. The prevalence of online platforms, microlearning modules, and adaptive training programs is likely to increase, empowering individuals to access pertinent training at their convenience, precisely when and where it is needed.

Adaptation, upskilling, and reskilling will be crucial to thrive in an increasingly AI-driven world for all parties involved. The evolving nature of work in the age of #AI shall make training more dynamic, on-demand, and focused on developing a broad set of adaptable skills.

Workplace transformation

#AI redefines workplace collaboration by enhancing interpersonal and multicultural communication, providing data-driven insights, fostering more efficient teamwork and innovation, as well as taking care of routine and repetitive tasks.

• Entrepreneurship support.
• Innovation involvement. AI is expected to boost employee involvement into innovation by automating routine tasks and enabling data-driven decision-making, freeing up time for creative thinking. As organizations embrace AI, a culture of innovation is fostered, empowering more employees to actively contribute to the generation of novel ideas and positive change.
• Participative leadership. AI enhances participative leadership by providing platforms for inclusive decision-making, empowering employees to actively contribute and share insights, thereby fostering a culture where everyone's input is valued and considered in leadership processes.