Gender Technology & Artificial Intelligence: Social Innovation and Corporate Governance

We are entering an Era of Innovation, transcending the limits of organizations, driving the emergence of Emerging Technologies. This trend makes us reflect on how the foundations of companies and the structures of societies were built. Now we need to model governance and planning to align business strategies in new regenerative models that meet the guidelines of the Sustainable Development Goals.

Consequently, technological and ESG skills have evolved, in the face of a market that seeks to be increasingly digital and sustainable, in dealing with ESG demands and digital dexterity not as mere obligations imposed by the market, but as business opportunities aimed at global competitiveness and the growth of small local organizations.

 This means investing in innovation and technologies that remodel processes and, mainly, cultivating an organizational culture that promotes innovation as a constant process in strategic planning for organizations to restructure themselves, increase productivity and competitiveness with positive and sustainable impacts.

The ability to understand and incorporate these skills into strategic planning is fundamental to the success of organizations, associated with the benefits of ESG companies, reflecting the growing importance of the economic sustainability of contemporary businesses, the creation of values, solid reputation and policies that promote Innovation Social and Corporate Governance.

 Social Innovation consists of new social technologies that allow both the promotion of social participation and ecosystem integration, as well as the promotion of social inclusion, equity, job generation, autonomy, empowerment, well-being and Human Development;

Corporate Governance refers to the system of rules, practices and processes through which companies are managed with transparency, innovation and ethics in decision-making. The governance structure also covers economic functions and activities with positive and sustainable impacts on the internal and external spheres of companies.

Previously, AI-based algorithms were mostly used in academic research projects, where their applications focused only on proof of concept, with little development in what could be future large-scale applications.

 Recent technological developments, the increase in the scientific community and also the exponential growth of resources allocated to this topic, have contributed to AI-based algorithms becoming essential and central tools, facilitating processes that were previously considered complex (Collins et al., 2021)

Today, there are vast opportunities that AI presents, but it is also crucial to maintain a strong ethical and security awareness in the use of data as we move forward. Because, in truth, the essential thing in this fast-paced era is that innovation is conducted responsibly, ensuring that technology “works” in favor of humanity

However, it is essential to recognize that these elements should not be treated in isolation, but rather as interconnected parts of a business strategy, targeting promising projects that are ensuring more inclusive and equitable environments;

However, new methods are needed that place Artificial Intelligence as cost-benefit strategies in actions in a safe, ethical and confidential manner, supported by security, transparency, an essential value chain to find a balance between fostering innovation with impact positive and sustainable.

Therefore, it is essential to configure and equalize the biases of unequal access to credit, public financing, the job market, entrepreneurship, wealth, rights and dignity; digital biases that contribute to the severe imbalance of personal, professional and intersectional competitiveness, built by the volatility of Racial Discrimination and Social and Gender Inequalities.

 However, there are gaps in gender data, which, in practice, have a disproportionate impact on the allocation of resources assertively, weakening cohesion, to the detriment of people belonging to discriminated and marginalized groups, affecting the chances and opportunities to prosper, in the opposite direction. and in comparison with the Sustainable Development Goals.

In the tendency to interact with new technologies effectively to complex social challenges, Gender Technology emerges as a scientific and emerging method in evaluating and helping to develop equity policies, the aim is to innovate social development strategies in a systemic way , with a positive and sustainable impact. Therefore, I measure the systematization of the flow of knowledge regarding gaps in Gender Transversality; scope of social risk vulnerabilities;

Women represent high levels of interconnected social vulnerabilities, which simultaneously cause damage and effects of a social, economic and democratic nature: in access to the health network, social security, job market, wage inequality and in decision-making in the political sphere; also highlighting the disparity in the asymmetry of women in leadership positions, in technological development, science and scientific research;

This complexity of negative impact includes racial and transgender discrimination, the adoption of more progressive tax measures for social return, the improvement of care policies, the absence of adequate social protections and the absence of robust assistance for victims of domestic violence, moral and sexual harassment in the workplace.

 Constantly, on top of the imminent effects of climate change and environmental disasters, there are disproportionate gender impacts. All of these risk factors can trigger irreparable damage to women's mental health and well-being and have a devastating local economic effect.

For Artificial Intelligence to achieve scientific singularity, it is crucial to transcend to the local reality in which people are inserted; measuring social changes and the emergence of new Cultural Identities, focusing on their experiences in the job market, social, political, economic and climate environments; enabling the use of Artificial Intelligence across the board; in the paradigm of contemporary systemic thinking.

The understanding of contemporary systemic thinking was formed only in the 1960s, through the pioneering work, Post II World War, by Bertalanffy (JUNG; ARANDA; TEN CATEN, 2009; WEBERING, 2016). Motivated by the occurrence of inexplicable phenomena in the area of biology, Bertalanffy generated an understanding that systematized theories not formally explained by the configuration of “organized complexity science”, with the “integrated all” approach (ULHMANN, 2002, p. 11). His work gave rise to a new systemic paradigm, which led to the disruption of objective thinking, dominated by the reductionist and causal method, contradicting dominant and rational thoughts.

 As it is a sociocultural phenomenon, there is a multiplicity of complex challenges, that is, integrated around gender inequalities, which expand in the absence of adequate social protections and the absence of packages or sets of intelligent public policies.

Given this dimension, the questioning always seeks to reflect on coincidence: since we live in a highly complex world, in which the circumstances of the causes and effects of the "polycrisis" are increasingly imminent to the socio-environmental challenges that we observe.

Therefore, I obfuscate that by attributing to the paradigm of contemporary systemic thinking, as a theoretical, scientific-regulatory and applicable method, to Artificial Intelligence, we will have great chances of providing positive social impacts, in modeling a more inclusive and equitable future. 

This process tends to be efficient and influential, as it governs the application of the "organized complexity theory", where the interaction and interdependence of the ecosystem results in a more solid and effective set than isolated and independent organisms.

Thus, through the automation of information processing, AI will develop complex systems that, when applied in organizations and society, will increase the performance, effectiveness and efficiency of internal information processing, in cooperation with sharing, "Open Science ," and the development of new Emerging Technologies.

Successive scientific processes structured the hypothesis of scientific evolution as a generator of innovation through the logic of processes and methods, guided by the systemic vision (JUNG; TEN CATEN; RIBEIRO, 2013, p. 1-7. 

In general, AI is considered a very comprehensive scientific area combined with the sub-area of Automatic Learning or, in English, Machine Learning (ML), which is consistent with predictive theory, in the systematization of new social scenarios and consistent with diagnostic analysis to identify the variables that influence the samples of the systemic data relationship, tend towards the perception of the local objective reality, the flow of knowledge algorithms, aimed at filling the gaps in gender transversality.

In this sense, AI is an instrument with a high tendency to impact Social Innovation in a positive and collaborative way, between increasing the level of access to the labor market, aiming at equity and the development of new social policy mechanisms, including in instruments of organizations' internal regulations, transforming the way different civilizations live, interact and develop their business models, referring to the high impact potential of Social Entrepreneurship. 

Within the scope of Corporate Governance, there is also reference to a high trend in strategic planning for positive and sustainable impact, since the company's social responsibility aims to improve understanding and awareness of the problems of social and complex challenges rooted in factors cultural and socioeconomic aspects of gender inequality in the job market, highlighting the high rate of violence and moral and sexual harassment in the workplace that affect thousands of women, affecting the victims' mental health and well-being.

However, for those who have database architecture in the integration of AI for the analysis of systemic data, singularities and the advancement of cybersecurity are necessary, this combination will contribute to the opportunity to transform data into valuable insights, in favor of an optimized business and in the development of new, smarter and more personalized products and services. 

These innovations offer a differentiated experience to customers and can be a measurable source for AI to impact business, covering the areas of sales conversion and customer retention, to financial return around economic sustainability such as customer engagement and loyalty. consumers, ultimately aiming to shape an equitable and sustainable prosperous future, with a focus on mental health, social well-being and female empowerment.

From a systemic perspective, to complex economic and social challenges, I enjoy science fiction, aiming at Artificial Intelligence linked to the principles and values of innovation, with a high futuristic tendency of Cognitive Models, capable of mobilizing society with behavioral changes to the intellectual precepts of Human Development and Gender Equality.

Above all, I refer to Emerging Technologies as a regenerative process, ahead of the causalities of gender inequalities, attributing Robust Equity Modeling as part of human and social evolution.