Artificial Intelligence: insights from the first meeting of the Daniel Research Group

By Andréia Santos

The perspective of creativity and innovation for technological purposes has always existed in society, respecting its capabilities and delimitations over the decades, ranging from the invention of the wheel to Artificial Intelligence, which is our main subject at Daniel Lab.

The idea of Artificial Intelligence – amazingly – was already thought of in Ancient Greece, by Aristotle about 300 years BC, albeit in a simple and primitive way, when he conjectured about the possibility of replacing slave labor for basic tasks such as sweeping the house, for example, by exchanging it for a broom with “devices” that allowed it to operate alone, having its own will and establishing a storage system[1].

Of course, it was impossible to put into practice at the time, but noting that the philosophical question into premature Artificial Intelligence is millennia old is, at the very least, motivating and intriguing. And this is how we feel, not only imagining the possibilities, but studying and developing ways of them becoming applicable and stimulating. Because what was once Aristotle’s idea, is today our reality, like cleaning robots or Robotic Housekeepers. So, what stops us from doing this, or even more?

Motivated by creativity and curiosity, we carried out surveys and studies on the applications available in the artificial intelligence market and the respective impacts that human-machine relationships cause and may cause on the economy, culture, society, race, gender, politics, health, and, more objectively, on the business environment.

In October 2018, the McKinsey Global Institute published a very interesting report on the promises and challenges for this era of Artificial Intelligence, which has been guiding our initial reflections and deserves to be highlighted throughout this text.

Looking at the business niche, the benefits of the technology in question pervade some areas, among them: (a) preventive maintenance, that is, the ability to generate forecasts, making the analysis of a large volume of data possible, such as audio and images, to detect anomalies in production lines, aircraft and medical diagnosis, for example; (b) logistical issues, such as optimization of traffic routing, optimization of assembly time and assistance in the efficiency and reduction of fuel costs; and (c) customer service, improving the care and experience for the public, by means of chatbots, which aim to reply to users’ demands and requests through artificial intelligence instead of a person.

The drive for innovation in the business environment makes this niche increasingly fluid and aggregating, seeking increased revenues, reaching and serving new markets, generating new types of products and services, influencing international trade and global data transfer.

However, in order to make artificial intelligence a global capital, the challenges involved in implementing tools based on this technological innovation must be seen, in order to expand the vision not just for the possible benefits, but also in the challenges and difficulties that, like every type of innovation, they bring to our society.

Although AI brings new professions and skills to the labor market in order to leverage productivity, public and private administrative structures must continually be innovating and following the market, investing in R&D and human capital, in order to make both business and political leaders and society itself digitally literate.

It should be recalled that the educational system itself must be rethought to overcome functional gaps that will naturally occur – it will be difficult for the rapid changes brought about by the technological innovation process to be absorbed with the same intensity and speed by the human mind, as the historian Yuval Noah Harari points out in his book “21 Lessons for the 21st Century”.

In addition, the very definitions of public policies and business strategies will suffer the impact of technological development. Invariably, both the public and private sectors should consider the dynamism of the labor market, the improvement in recruitment processes, the expansion of forms of working, regulatory aspects, social norms and social acceptance to rethink transition and security models for workers who do not develop the skills necessary for this new reality.

In 2017 and 2018, Finland implemented a basic income program for unemployed citizens in order to ascertain what social assistance should be in the computer age. Its application, although experimental in form, divided opinions[2].

With respect to the social acceptance of Artificial Intelligence, it can be seen that it is directly linked to public policies that seek, above all, to disseminate knowledge to users about this new society that has been created around technological functionalities and that promote and protect fundamental values and human rights such as privacy, affording consumers self-determination of information (one of the main pillars of the Brazilian Data Protection Act).

Jointly, social well-being, universality, transparency and freedom with respect to gender, color, ethnicity, physical or mental impairment and sexual orientation should be ensured, with a view to solving existing problems such as deep fakes, cyber security, biased criminal justice systems, and misuse of bots for social media misinformation.

Recalling that such public policies should promote incentives for innovation, balancing ownership interests and other intellectual property rights for the business sector in favor of free enterprise, free competition and economic development.

Another relevant point is that Artificial Intelligence was initially developed to solve specific problems. In the midst of so many new ramifications, applications and societal needs, it needs to be reviewed from a multidisciplinary perspective, including philosophical and sociological. How are humans and machines to be integrated in the same environment?

A practical example that shows us the unconstrained progress of Cognitive Intelligence is the case of Watson, IBM software that has gradually been growing in the market. The platform, directly connected to the network, has access to articles and research to accumulate intellectual capital, as well as direct learning with human contact that allows a broad intelligence on specific subjects, calculating probabilities and affording options in the allowed subjects.

Today, Watson provides value-based solutions to optimize performance and manage more assertive choices. This is the case with Watson Health, which provides effective health management assistance, diagnosing sick people, assisting in drug research with Watson for Drug Discovery and supplying genetically accurate medicine with Watson for Genomics.

Aside from the healthcare industry, IBM also offers the Watson Financial Service, which will primarily help banks meet regulatory expectations in areas such as money laundering and consumer complaint databases, learning and updating critical information, and ingesting more information when created. IBM has also been enhancing Watson for cyber security with integration into corporate security operations.

Through such transformations, current and coming, we must always be alert and stimulated to think about the applicability of these technologies to our social environments, observing the faces of this evolutionary process and investigating its execution in favor of Artificial Intelligence that is diverse, concise and effective, leaving aside that depreciative perspective of a “Skynet” as in “Terminator”. May we be actors of a humanized and molded digital transformation for the common good.


[1] BBVA. What would Aristotle say about artificial intelligence? Available at:

[2] El País. Finland completed a universal basic income experiment with ambiguous results. Available at:



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