Machine Learning provides sustainability

 5 minute read

In the era of big data, the definition of sustainability goes beyond eco-friendliness. Education, knowledge, and well-weighted decision-making become its constituents. Finding a compromise between long-term goals and immediate desires is a novel value of the upcoming century. Machine learning, digital humanities, and providing a motivating environment for education are the instruments modern cities will use to compete for talented labor, thrive economically, and come up with green solutions. Attracting smart people is an innovative way to boost economic development and become a globally competitive city.

Making Knowledge Available for All

Decoding and analyzing the languages is essential for global communication and carries an important historical value. Digital humanities might seem a surprising application of Machine Learning in humanitarian sciences. Nevertheless, the mix of digital and humanitarian sciences boost the progress in social studies. Library of Congress creates digitized archives to collect all important information and analyze historical events to see an analogy between present and past and determine forces triggering certain behavioral responses. Similarly, the Unicode Consortium introduced an approach to decoding ancient languages, and soon texting with hieroglyphs ought to be possible. Finding similarities between linguistic structures empowers deep learning and assists in faster language acquisition.

In turn, the application of ML in literature allows people reaching and comprehending the mastery of writing. TextRank analyzes Conan Doyle’s books and the occurrence of specific words in the text by helping people improve their self-expression. This application of ML and AI makes big data equally available to scholars and regular Internet users. Deep learning and high access to information bring cultural heritage and social behavior close to people leading to the higher educated society of decision-makers with knowledge for all – logic, sustainability, and intelligence gain their strength.

Era of Entrepreneurs and Agile Learning

Data access, digital humanities, e-courses, and various technological opportunities give a kick off to e-learning sphere with 23% growth every year. Nowadays, 74% of people use mobile devices for their education and self-development. The adoption of e-learning tools has already started and usage of AI and ML in the educational sector is projected to increase by 47.5% by 2021 whereas 18% of training budget is spent on e-learning solutions. With ML utilized for continuous analysis of teacher-student interactions and one’s learning patterns, customized open learner model becomes a reality. Machine Learning is used to continuously discover one’s needs and preferences, comply with them, and cultivate knowledge-exchange. There is a number of applications using the digital intelligence for education. “The recent developments in AI and machine-learning are a major exception with the potential to revolutionize how young people learn, teachers and tutors teach, and how society drives forward learning in the future,” says Ian Fordham, chief executive of Edtech UK, the strategic body for ed tech. Products like Third Space, that provides real-life feedback to teachers, is a tool for educators to concentrate on their students and empower them in the learning process. At the same time, Whizz Education, conceptualized virtual math assistance, claims that an hour a week with their app can accelerate a student’s learning by 18 months ahead of their peers. there is a potential for ML to be used as a tool or as an educator directly bringing customizable learning solutions to an entirely new level.

After all, throughout the life, there are different educational needs of a population. Advanced training, as well as basic education, raises the bar of critical thinking that creates a new society with sustainable thinking. ML uses algorithms for knowledge-systematization giving a new retrospective to sustainable decision-making. In this case, people give priority to long-term goals rather to short-term desires. Agile learning centers enable cultivating joy from learning and creating a vibrant community and environment for education. With new agile management tools like an emphasis on self-motivation, direction, and flexibility, students will adapt to the arising era of entrepreneurial culture. Becoming emotionally intelligent, self-aware and motivated will lead to a positive attitude towards learning. Smart and ecologically-oriented are new definers of competitive employees. The Epoque of smart sustainable long-term decision-makers is on its rise with ML as a progress trigger.

Cities Competing for Smarter Labor

The new educational opportunities and needs for more mature workforce trigger changes to the education system. Countries consider starting an educational process as early as possible – France views new school age as 3 years old, New Zealand – 5 years old. One of the rationals for it is staying competitive at the international arena and educating a new generation of talented individuals and change agents.

Intensifying competition for a smart workforce with sustainable mindset incurs also at city levels. According to the UN, the global urban population will increase by 67% with 2.4 billion more people becoming city citizens by 2050. This accelerated upsurge will require cities developing new sustainable solutions and attracting talented labor more on the urban than national levels. These will become keys in reaching economic prosperity and sustainability and new way to compete and gain desired GDP upsurge and global ranking. How can megapolises attract the new intelligent labor? By respecting the sustainable and wellness demands of new generations. Cities have to concentrate on societal and ecological developments as well as educational opportunities for the next age groups. The future is “smart” driving to the era of profoundly evaluated decisions, minimized risks, and substantial focus on the environment and sustainable solutions for urban designs, infrastructures, and social organization.

Insight Box

ML intervention in a diversity of areas now increases the accessibility of information and makes it available equally for all people with the basic Internet access. Meanwhile, agile learning model raises a new generation of decision-makers, who perceive long-term goals, sustainability, and self-motivation as new values and are ready to take risks to change the world in a positive way. Talented labor and knowledge-ownership are the driving forces of progress and desired characteristics for job seekers and future professionals. Investing in high-quality interactive education becomes a priority, and reaching the sustainable future of the modern cities with the smart and educated population as their driving force is perceived as upcoming “present” rather than futuristic reality from science-fiction.

#eco city competitiveness #future trends #intelligent labour #machine learning #ML #sustainability
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In 2007 global urban population exceeded global rural. This means that over half of the world’s population lives in urban areas and is responsible for over 70% of global greenhouse gas emissions. With the growth of population most of the world is going to be build or rebuild in nearest two decades.

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