Impact of Machine Learning in Unlocking Human Potential
In the digital age, Artificial Intelligence(AI) has indefinitely become one of the largest innovations, existing in the Face ID of a mobile phone to the auto drive function available in various modern, state-of-the-art cars. When people merely want to manage their time more effectively, in-built tools are present to analyze work patterns, calendar events, and even slow email communication. In situations where one wants to translate their accented French into English, only a simple google search — embedded with NLP (Natural Language Processing) is required. The sense of interconnectedness throughout the world is only possible through the internet and social media platforms that allow for frequent exchange of diversity from foreign land.
Now, aside from all this ease of comfort ‘generated’ by these futuristic machines, the real question to speculate upon is this — how does such innovation inherently make us better human beings? Day by day, we are being sucked into the world of shallow-work — work that doesn’t require deep thinking — that don’t necessarily promote cognitive engagement. In the Machine Learning environment, the term is coined as shallow learning: using simple mathematical-based algorithms with a use of a small number of layers. They are not modeled to capture and interpret complex data patterns, just like our brains after reliance on so much automation.
Nevertheless, according to G. Siemens, artificial cognition can combine human intelligence with machine learning models to make groundbreaking innovations.
DeepMind has also developed an AI system called AlphaFold to predict the 3-D structure of proteins based solely on their amino acid sequences (G. Siemens et al., 2022).
The problem of “predicting protein structures…has challenged scientists for decades”, and with such technology could make discoveries that integrate in “human decision making” (G. Siemens et al., 2022). Integrating machine learning into our cognitive abilities essentially allows us to perform deep learning tasks in an environment of shallow work. Another scenario of such collaboration is the “‘Human In the Loop’(HITL)…human is always part of the process and consequentially influences the outcome of the interaction” (G. Siemens et al., 2022).
Such inspiring cooperation between human cognition and artificial intelligence effectively contribute to the personal growth of individuals by making their services easier while also not having a full reliance on this new technology.
Works Cited
Siemens, G., Marmolejo-Ramos, F., Gabriel, F., Medeiros, K., Marrone, R., Joksimovic, S., & de Laat, M. (2022). Human and artificial cognition. Computers & Education: Artificial Intelligence, 1, 100107. https://doi.org/10.1016/j.caeai.2022.100107
