Skip to main content

Robot Automation

10 Jobs Most At Risk From Automation and Robotics in The UK

Nowadays, one of the hottest topics is the significant number of jobs at high risk of automation. This article presents the top high-risk jobs in the UK, based on statistics collected from the National Statistics Board of the UK government. 
Repetitive and Manual Jobs:
Jobs involving repetitive, manual duties are at the highest risk of mechanisation.
Routine-Based Positions:
Positions that do not require substantial decision-making or creativity are more susceptible to automation.
Technological Advancements:
The rise of robotics, AI, and machine learning significantly contributes to the automation of these roles.
Impact on Low-Skilled Positions:
Many of the high-risk jobs are in sectors that traditionally employ lower-skilled workers.
10 Most Jobs at Risk from Automation and Robotics in the UK:
Waiters and Waitresses
  • Probability of Automation: 72.81%
  • Significance: High-risk due to repetitive tasks that can be efficiently automated by robots and AI.
Shelf Fillers
  • Probability of Automation: 71.70%
  • Significance: This role involves manual tasks that can be simplified through automated procedures.
Elementary Sales Occupations
  • Probability of Automation: 70.69%
  • Significance: These roles often involve basic sales duties that can be replaced by self-service kiosks and e-commerce platforms.
Bar Staff
  • Probability of Automation: 70.66%
  • Significance: Similar to waitstaff, bar roles are vulnerable to automation through robotic bartenders.
Kitchen and Catering Assistants
  • Probability of Automation: 69.20%
  • Significance: Routine food preparation and cleaning tasks can be managed by robotic kitchen tools.
Farm Workers
  • Probability of Automation: 69.05%
  • Significance: The increasing use of automated machinery in farming puts these roles at risk.
Sewing Machinists
  • Probability of Automation: 68.64%
  • Significance: The repetitive nature of sewing tasks makes them highly automatable with modern machinery.
Cleaners and Domestics
  • Probability of Automation: 68.13%
  • Significance: Mechanisation in cleaning, such as robotic vacuums, reduces the demand for human cleaners.
Tyre, Exhaust, and Windscreen Fitters
  • Probability of Automation: 68.07%
  • Significance: Jobs in this sector can be replaced by advanced machinery and computerised systems.
Vehicle Valeters and Cleaners
  • Probability of Automation: 67.77%
  • Significance: Automated car washes and cleaning systems can perform these tasks without human intervention.

Approximately 1.5 million careers in England are at high risk of having some of their tasks and jobs automated in the future, according to an investigation by the Office for National Statistics (ONS). 

gov.uk/employment_risk


Comments

Post a Comment

Popular posts from this blog

Vaccine Hesitancy in the UK

Vaccine Hesitancy in the UK Israt Jahan   2 December 2021 University Of Edinburgh Narrative Target Audience: Our primary target audience for this study is the Black British community across the UK. We are specifically addressing individuals who have expressed hesitancy regarding COVID-19 immunisation. However, the findings and insights presented in this study are relevant and valuable to the general population of the UK who may have reservations about receiving the COVID-19 vaccine. Data Source:   The data utilised for this research was sourced from the John Hopkins data repository. We meticulously examined COVID-19 data pertaining to the United Kingdom, with a particular focus on various key metrics. These metrics encompass confirmed cases, the count of individuals who are fully vaccinated, those who are partially vaccinated, individuals who have recovered from the virus, and the case fatality ratio. Type of Data:   The data employed in this study falls under the ca...
Post a Comment
Read more

The Most Significant Concerns with AI Finance

 The Most Important Concerns with AI Finance The financial industry has seen a tremendous upheaval thanks to artificial intelligence (AI). AI finance has made new opportunities possible thanks to its capacity to analyse enormous volumes of data, offer real-time insights, and automate difficult operations. However, it has its share of difficulties and possible issues, just like any other technology. The biggest obstacles to implementing AI in finance will be discussed in this blog post.   Lack of Transparency Challenge: Deep learning models, in particular, can be complex and challenging to interpret. It may be difficult to understand how AI came to a particular recommendation or choice due to this lack of transparency. The answer: Work is being done to create explainable AI (XAI) methods that shed light on how AI makes decisions. Building trust requires selecting AI solutions that put an emphasis on transparency and interpretability. The handling of private and confidential fi...
Post a Comment
Read more

Cancer Research Image Classification: Exploring Machine Learning Techniques

KaggleCancerImagesDataForML   Precision Diagnosis and Prognosis: Revolutionising Cancer Research Numerous noteworthy advantages of machine learning in cancer research contribute to improvements in knowledge, diagnosis, treatment, and overall patient care. The following are some main advantages:                          Early Diagnosis and Detection for  Cancer Research :   Large-scale medical data, such as genetic, imaging, and clinical data, can be analysed using machine learning algorithms to find patterns that point to cancer in its early stages.Early detection increases the likelihood of positive results by enabling less invasive and more effective treatment alternatives. Revolutionising Cancer Treatment through Personalised Medicine: Advancements and Breakthroughs in Cancer Research :                Machine learning assists in the analysis of patient data to pinpo...
Post a Comment
Read more