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“The only place where success comes before work is in the dictionary.” – Vidal Sassoon
PROBLEM: PUTING AI TO THE TEST
Like the Turing Test, there has to be another practical work related test for the usefulness of AI to business.
The simplest way of sampling this is simply to select a random Top Ten of employment types and find out if and how well AI is being adopted at the coalface.
REFERENCE: THE UNDERCOVER BOSS AND WORK STUDY
Work studies that learn from the coalface are invaluable in business, as demonstrated by pioneers like Frank Gilbreth who developed techniques to analyse and improve work processes through detailed observation. These studies have evolved to encompass various applications, from optimising production processes to enhancing workplace safety and employee satisfaction, continuing to offer critical insights for improving organisational performance and employee well-being.
SECTIONS OVERVIEW
So here are 10 jobs that have are being transformed from the bottom up by AI:
- NURSES
- CHEFS
- ARCHITECTS
- ENGINEERS
- AUTHORS
- CARPENTERS
- POLICE OFFICERS
- WINDOW CLEANERS
- GARDENERS
- ELECTRICIANS
SECTIONS
- NURSES
Remote Patient Monitoring and Telehealth: AI supports remote patient monitoring and telehealth services, enabling nurses to manage patients’ health outside traditional healthcare settings. This not only enhances patient access to care but also allows nurses to monitor patients’ conditions remotely, potentially preventing hospital admissions and reducing healthcare costs.
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- CHEFS
Menu Planning and Personalisation: AI assists with menu planning by considering local traditions and available products. It can also personalise dining experiences by analysing customer preferences, dietary restrictions, and past meal histories to tailor menus and recommendations.
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- ARCHITECTS
Creating More Sustainable Buildings: AI analyses Building Information Modelling (BIM) designs to estimate carbon emissions and suggests ways to reduce them, including alternative materials and design changes for improved energy efficiency.
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- ENGINEERS
Predictive Maintenance and Problem-Solving: AI provides powerful tools for predictive maintenance, allowing engineers to anticipate equipment failures and prevent downtime. Additionally, AI helps in solving intractable problems by offering innovative solutions based on data analysis and predictive modelling.
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- AUTHORS
Plot Development and Character Creation: Some AI tools are designed to help with plot development and character creation, offering suggestions for story arcs, character motivations, and dialogue. This can be particularly useful for authors struggling with writer’s block or seeking to experiment with new narrative structures.
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- CARPENTERS
Optimised Material Usage: AI algorithms optimise material usage by suggesting the most efficient cutting patterns based on project requirements and available materials. This reduces waste, minimises costs, and lowers the environmental impact.
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- POLICE OFFICERS
Facial Recognition Software: AI-assisted decision-making, particularly through facial recognition software, allows law enforcement to quickly identify suspects, potentially saving hours or even weeks of investigative time. This technology acts as an investigative assistant, complementing rather than replacing traditional investigative methods. It requires further verification through other evidence to substantiate suspicions raised by AI-based matches.
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- WINDOW CLEANERS
Optimisation of Cleaning Routes: AI can analyse factors such as weather conditions, traffic, and building occupancy schedules to optimise the order in which windows are cleaned. This ensures that resources are allocated efficiently, minimising downtime and maximising productivity.
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- GARDENERS
Automated Monitoring and Adjustment: AI systems equipped with smart sensors can monitor soil conditions and automatically adjust watering, temperature, and humidity settings. This automation saves time and ensures optimal growing conditions for plants, reducing manual labour and increasing productivity.
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- ELECTRICIANS
Advanced Diagnostics and Smart Energy Solutions: AI evolves to offer advanced diagnostics, automated installations, and smart energy solutions. Integration with IoT leads to homes and buildings where electrical systems are fully integrated, self-diagnosing, and self-correcting, making electrical work safer, more efficient, and aligned with the needs of a rapidly evolving world.
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IMPLICATIONS: TRICKLE UP EFFECT
The opposite of the trickle-down effect is known as the trickle-up effect, also referred to as bubble-up economics. This economic policy proposition suggests that direct benefits to lower-income individuals can stimulate national income in an economy. Essentially, it posits that policies aimed at assisting those at the lower end of the income spectrum will positively impact society as a whole, with these benefits eventually trickling up through the population. This contrasts with trickle-down economics, which argues that benefits to the wealthy or large corporations will indirectly benefit the wider economy and society.
Trickle-up economics emphasises the importance of starting economic initiatives at the grassroots level, focusing on the needs and empowerment of lower-income individuals. This approach is often associated with policies that aim to increase the purchasing power of consumers, believing that this will lead to increased demand, which in turn stimulates economic activity and growth. Examples of policies that reflect this approach include the Obama administration’s actions and Biden’s American Rescue Plan, which were characterised by significant spending programs aimed at boosting the economy from the bottom up.
This concept challenges the traditional view of economic growth originating from the top down, advocating instead for a more equitable distribution of wealth and opportunities. Critics of trickle-down economics argue that focusing on the wealthiest segments of society may not effectively stimulate the broader economy, as the benefits do not necessarily “trickle down” to the middle and lower classes as intended. Instead, they advocate for policies that directly address the needs of lower-income individuals, believing that this approach will more effectively stimulate economic growth and improve societal well-being.
