Hedging Employee Skills/Talent to Leverage AI

The key to a company’s successful AI transition is to hedge its employee’s skills. In McKinsey’s Global Institute recent analysis of the current state of automation, human-like capabilities were rated according to a three-tier capability scale: Below median, Median, and Top quartile.

Arts vs. Science of Decision Making

Decisions and the courses of action from these decisions is both an art and a science. Objective machine data or technical rationalism and human tacit knowledge and heuristics otherwise known as reflective constructivism must come together to form a collective decisions in areas such as design and planning.

Tacit Knowledge/Wisdom: Path to Success

According to www.knowledge-management-tools.net, tacit knowledge as different from explicit knowledge is intuitive know-how, that which is rooted in context, experience, practice, and values. It is hard to communicate and typically transferred through socialization and mentoring.

From Strategic Vision to Action

The gathering, analysis, and strategic actions derived from big data is becoming a standard business and management protocol. The Harvard Business Review focused on the revolution as their feature article in October 2012. The process of data analytics is similar to the processing of refining any resource from raw material state to finished product state.

How to Objectively Evaluate Employee Productivity

The methods and traditional tools that are used by Human Resources to assess and appraise employees range from limited and ineffective to biased and error-prone. Much of the traditional HR employee appraisal process is steep in human subjectivity and therefore interpersonal bias and human errors.

Profit Is No Longer The Only Purpose

The rising popularity of profit/purpose driven organizations is the outgrowth of this internal re-examination of priorities and purpose that individuals and by extension, organizations, have struggled with over recent years. The distinctions between not for profit charities or solely purpose-driven entities and for profit corporations or solely profit-driven entities have blurred.

Machine Learning Enhances Employee Performance

Machine learning offers tremendous potential not just within the workplace but more widely within the evolution of society’s human values (in terms of rights, ethics, laws, social norms, privacy, fairness, and social contracts) and technology at large. Machine learning occupies a unique position of evaluating human values while simultaneously creating human value expectations

People Are Good At Handling Exceptional Cases

Humans do possess certain advantages that remain elusive to robots now. The dominant human advantages include attributes such as flexibility and adaptability. The body of knowledge that humans have acquired is impressive. Indeed, this idea of the accumulation of knowledge bodes well with the argument in favour of retaining older workers.

Repetitive or Rule Based? Robots Are Better

Within a repetitive working environment where the tasks and activities can be distilled into a set of rules, robotic automation will consistently outperform human workers. But a more controversial question is whether the robots are also better at doing tasks that require decision making.

Organizations vs. Markets is Dictated by The Culture of a Company

Other studies have parcelled out the variable of organizational culture as a factor in the performance of the organization. In a study completed by Cameron and Quinn, called “The Competing Values Framework”, the researchers produced a chart with Focus on the x-axis and Structure on the y-axis.

Focus Should Be On Activities

This changing work landscape which has been initiated and popularized by technology firms to create workflow efficiencies and to adapt to their respective competitive environment, has been deemed overwhelmingly successful. It is difficult to argue with the quantum growth of the likes of Google, Apple, Facebook, and Amazon as they have leapfrogged beyond the valuations of the traditional industrial conglomerates.

Currently Employees Are Organized Based on Their Roles

The classic organization chart is role based and categorized according to business functions. These functions or departments have their own linear hierarchies. Future organizational charts will be less rigid, less hierarchical, and less vertical.

Is This Time Different? Why Now?

According to AMP New Ventures, previous attempts to bring AI into the mainstream have been thwarted by various systemic factors including technological advancements and economic costs. Today the computational and technology environment is ripe for the launch and the adoption of AI.

The Looming Threat to Companies

Survival, according to evolutionary theory is at the crux of all natural and man-made systems. Man-made companies must accept the immanence of AI as a potentially disruptive factor in their business. With this clarity, companies must then take steps to not only survive but to thrive from this new world order.

Emergence of Artificial Intelligence

Artificial intelligence emerged in 1950 when the renowned computer futurist and thinker Alan Turing published a paper that described the concept of machine intelligence. Turing’s concept of machine intelligence evolved a few years later to “artificial intelligence”.