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How AI is Making Research Easier but Policymaking Harder

Artificial intelligence (AI) is only just beginning to penetrate the workplace, prompting executives to rethink their corporate governance. Many of the tasks that make up today's jobs will be taken over by AI. Whether it is replacing workers with computer-controlled processes or machines being able to make complex decisions and perform tasks normally reserved for people like artificial intelligence, the way work is done is changing. Artificial intelligence is increasingly becoming a threat to jobs that were once human domain, making it harder for humans to stand up to machines.

Rather than replacing jobs, robots and other AI systems can also improve people's knowledge and skills to work better and work more efficiently. By understanding themselves before they join a robot, human workers can focus on working with the robot to achieve better results. 

It’s true: AI systems are certainly helping make everyday work more efficient. If you want to see proof, just reread the first two paragraphs of this blog post. It’s almost impossible to tell, but they were written completely by an AI-powered bot called “AIWriter”.

This AI-powered bot is capable of creating an 800 word article from just a 6 word prompt - “How Will AI Make Work Easier?”. AI Writer is available to use at (https://panel.ai-writer.com).

Apart from just writing blog posts, there are seemingly limitless applications for AI software to optimise the work we do in almost any industry. AI powers Spotify’s data-driven music recommendation engine; it has been applied to streamline the process of language learning on platforms such as Lingwing; and, it has even been used to give personal advice and recommendations designed to boost the well-being and mental health of smartphone users via apps like uMore.

This AI-powered bot is capable of creating an 800 word article from just a 6 word prompt - “How Will AI Make Work Easier?”. AI Writer is available to use at (https://panel.ai-writer.com).

It therefore shouldn’t come as a surprise that investors are stepping up their investments in companies leveraging machine learning as part of their product. For the better part of the decade between 2011 and 2018, approximately $50 billion has been invested by venture capital funds in AI start-ups.

Some industries are raring to reap the rewards of more efficient work and are welcoming AI applications with open arms, while others are hesitant to make such welcoming approaches. One field in particular that's beginning to converge with AI is psychology.

AI and the mind

Researchers Flávio de Mello and Sebastião de Souza have proposed a hybrid approach of using Psychology and AI to assist therapists through the use of computer implemented tools, which may allow combining heuristics and algorithms in a complementary way to the benefit of patients. In my own line of work as the Chief Scientific Officer of uMore, such AI-based tools are being used to design a recommendation engine which gives users the psychological advice which will best benefit themselves as individuals.

Even in terms of research, Fernand Gobet and Giovanni Sala argue that current AI technologies can be applied to design complex simulated environments which enable researchers to study creative thinking. This could help provide a much more valid approach to studying creativity in real world settings, as opposed to unsophisticated and insular learning environments currently used in laboratories.

During the process of writing this article, I have also relied on AI to enhance my ability to summarize all of the source material acquired from my initial research of the topic. Using genei to help condense long articles and create high-quality summary notes, I have been able to write this article in a fraction of the time in which it normally takes me.

The ethics of AI and policymaking

It is becoming abundantly clear that the use of AI is improving the efficiency of the work of psychological researchers today, while also offering enticing prospects for future methodological improvements. As we begin to move towards this convergence point between both fields, it will however be essential to consider the ethical implications of its usage. Oftentimes, we are unable to fully predict the negative externalities resulting from technological innovations. It would have been difficult to predict that Facebook’s original 2008 mission of “helping you connect and share with the people in your life” could have led to opportunities for groups such as Russian hackers or Cambridge Analytica to influence the results of key elections an entire decade later.

Thinking of a fairer future, an interdisciplinary approach led by software engineers, researchers and policy makers must define how we will use AI to improve our lives. Will we reap the rewards of increased personalisation, or will we become increasingly solitary and isolated when online? Will data be used to improve the quality and the efficiency of services we use, or will it breach our personal privacy and informational online makeup? Will AI be used to make our lives easier, or will it continue to cause headaches for the very software engineers, researchers and policy makers who shall shape these ethical frameworks?

It would be easy to say that time will soon tell. However, as early adopters of such technologies, we can choose to either support or neglect the companies who use AI to help make our lives easier. Technological literacy is becoming more important each year as we begin to transition to a society which uses AI to optimise the work which we do. The question is, will our relationship to such services yield only short-term benefits or will we co-create a future alongside the support of AI that can provide lasting benefits for all in the years to come?


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