Can We Use AI for Good in Everyday Life? A Call to Action for a Human Ecological Approach
By Soyeon Shim, Dipesh Navsaria, Lori DiPrete Brown | December 2025
Of course, AI is not entirely new, and neither are big changes. Humans have incorporated world-changing discoveries into our civilization before – fire, the wheel, the alphabet, the printing press, the washing machine, the internet… But the speed and scale of this technological transformation into every aspect of our daily lives clearly holds both promise and peril. While the term 'artificial intelligence' can refer to a number of technologies, here AI refers to large language model generative AI systems commonly in use today, e.g. ChatGPT, Gemini, Claude, and others. We believe that this kind of artificial intelligence requires human-centered approaches that center holistic wellbeing. If left to the technical experts and the “invisible hand” of the marketplace alone, this transformation is not likely to optimize benefits, or distribute them fairly. Rather, AI efforts must be designed with intention, wisdom, care and a deep understanding of the relationship between humans and their environments.
What would it take to design AI so that human communities, and all forms of life, can thrive?
Cautious observers of the rapid rollout of AI remind us that effective leadership requires eyes-wide-open integrity – the courage to name and face the risks, downsides, and potential unintended harms of AI related to psychology, equity, environmental impacts, and the sheer pace of change.
Here we propose that it takes just as much courage, if not more, to discern, with ethics and science, what it would take for this process to go well, and to take responsibility for making that reality happen – to optimize the impacts of AI with a focus on wellbeing, equity, and care of the earth. This is where human ecology has a unique role and responsibility.
Human ecology is the interdisciplinary study of relationships among people, the natural and built environments, and the systems of care and meaning that sustain life. It examines how families, communities and ecosystems interact - how change in one part of the system ripples through the rest. At its heart, human ecology is about interdependence: the idea that wellbeing depends on the health of the whole.
Are our leaders from medicine, engineering, education, agriculture, or other fields ready to use AI for good and avoid harm? Rigorous transdisciplinary thinking will be needed – and the discipline of human ecology can play a critical role in the conversation.
Recently, the School of Human Ecology at the University of Wisconsin-Madison convened a diverse group of teachers and scholars from a range of disciplines to explore the role of AI in society, and the opportunities and responsibilities for human ecologists. No doubt similar conversations are beginning at schools and departments of human ecology around the world. We anticipate a growing convergence around the idea that the future of AI cannot be left to technical experts or market forces alone. It must be a shared project of co-creation among scientists, educators, policymakers, families and communities.
As national conversations and the agenda for future scholarship emerges, we want to underscore the important contributions of human ecology as a disciple and share the ideas that are guiding our work at UW-Madison. We hope to spark dialogue about ethical leadership from within human ecology, across disciplines and throughout the public and private sectors.
How can human ecology help us to address the opportunities and challenges associated with AI in a rapidly changing world?
To understand what’s at stake, it helps to start from the ground up – from the rhythms and routines of everyday life. Human ecology considers how people and environments interact across the full spectrum of daily experience: family, community, work, education, economy and planet. When applied to AI, this approach changes the conversation. Instead of asking, “What can artificial intelligence do?”, human ecologists ask, “How can humans use AI to promote thriving for all?” This shift defines the human ecological perspective.
Human ecologists use their expertise in the social sciences and design to advance human thriving, taking into consideration relationships between humans and their environments – this includes the digital realm. This holistic socio-ecological approach derives its strength from intentional perspective-taking and a multi-scalar lens that considers home and kinship networks, community and society. Human ecologists are action-oriented; employ participatory processes; and center equity. Getting AI right means grounding our work in lived experiences, and developing the ability to consider different perspectives, and learning to live in relationships, reciprocity and care with our neighbors – those who are like us, and those who are different from us.
Human ecology is essential when facing rapid societal transitions – from fostering health in family and community life, to addressing climate change, to peace-making. As artificial intelligence rapidly becomes part of daily life - the human ecology community has begun to articulate areas for action.
Human Connection and Relationships
Will AI supplant essential human interactions, leading to social isolation, or will it allow people to connect meaningfully across place, language, and time? How do we find the right balance of in-person interactions and virtual engagement, so that technology doesn't mediate all aspects of life and work?
In ecological terms, social isolation is a form of habitat loss; AI must help preserve the social habitats that sustain human thriving.
Education and Skill Development
Parents and educators at all levels must think critically and level up their own skills to get AI in education right. How can AI foster critical thinking, creativity, and problem-solving skills, while avoiding the harms associated with digital addiction, physical inactivity and social isolation? Because of, alongside, or in spite of AI, how can we create systems where teachers and parents can develop deep relationships for mentoring and nurturance.
Learning ecosystems thrive on relationships — teachers, peers, families — not algorithms alone.
Social and Economic Equity
How can we create good jobs for all in an AI-infused environment? While changes in how we work are inevitable, how can this be done collaboratively, with an eye towards a triple bottom line that includes economic prosperity for all, overall human thriving, and care for the earth and all forms of life. Rather than accepting widespread job loss and increased financial insecurity, AI could be used (alongside other social change and innovation strategies) to reduce societal inequalities and make life better. How can we foster and develop a civic culture, and related laws and policies that enable AI that truly serves the common good and contributes to equity in our market systems?
Equity is not a secondary goal but a primary measure of system health; disparities signal dysfunction in the human ecology.
Ethics and Guardrails
A recurring theme is the need for an ethical framework and guardrails to prevent and mitigate harm. How can governments, universities, and both the private and non-profit sectors build their capacity for human well-being and the environment? How can accountability be built into design, planning and implementation?
Ethical AI is not just about rules of use but about the right relationship among humans, institutions, and the earth.
Environmental Impact
Many aspects of modern life, from the automobile-centered transportation systems, to the use of air conditioners, to inefficiencies in production and distribution in food systems, are designed without including responsible resource use as a design criteria and without calculating environmental degradation into their costs. Human ecologists can contribute to the development of life-centered design principles and life-centered metrics that capture the true flow of resources, so that AI deployment is environmentally sustainable and just.
AI’s footprint reminds us that every digital action has an ecological shadow.
How can we co-create systems of care that embrace innovation and provide needed safeguards to support positive human interactions at every stage in the lifecourse?
Across these domains, one theme persists: AI is not just a tool; it is an integral part of our ecosystem. Its development and use must reflect the same principles that sustain any healthy environment — reciprocity, balance, feedback, and care. Co-creation means inviting the full ecosystem of stakeholders — families, educators, engineers, designers, policymakers, and citizens — to shape technology together. It means crash-testing innovations for harm before wide release, learning from lived experience, and adjusting course as feedback emerges. It means designing for human thriving, not merely efficiency or profit. In the language of human ecology, co-creation is not a metaphor. It is a method — a way of living wisely with change.
An examination of innovation in human history uncovers a constant struggle between caution and rapid diffusion. An overly-cautious approach, while warily looking for risks and problems, may also paradoxically cause harm by withholding new ideas, techniques, or approaches that may improve human lives. At the same time, unfettered adoption of new innovations may rapidly advance the state of affairs in numerous fields of human endeavour, but again may also result in deleterious unforeseen consequences.
As an imperfect but useful analogy, let us consider pharmaceutical development: an overly-cautious approach could have a very real impact on people by withholding medication that could literally save lives. On the other hand, a laissez-faire mindset could result in, at the very least, ineffective pharmaceuticals, and potentially life-altering or deadly side effects. In the United States — as well as other industrialized nations — there is a network of approaches regulating the development of medical products, a stringent set of requirements around human subjects research, a clear requirement for proof of efficacy and enumeration of unintended effects, and of transparent reporting.
Unlike drugs and medical devices, which are regulated through highly complex systems of review, research, and monitoring, AI has essentially no meaningful regulations. This is not necessarily unique to AI, but is largely true of the digital world — similar questions are routinely posed around social media, smartphones, and internet usage in general. It is no surprise that the pace of innovation — and diffusion — around AI is even faster than the other digital systems mentioned above, and not only does that speed stymie possible policy and regulatory approaches, but our ability to have societal conversations about how even to think about it.
The question, critically, is not how we impede innovation, but rather how do we co-create systems that bring out the best of innovation while ensuring that positive human interactions are being not only unhurt, but across the lifespan? Strangely, we appear to be largely in a “flipped design” process, where the base tools are being created and then subsequently we seek solutions for the tools to be applied to.
What is not happening yet is a widely-scaled process where we look at the challenges and opportunities, and then design the tools needed for solutions. AI systems are not incompatible with an outcomes-oriented approach — in fact, they may operate better by doing so. As a brief example, asking a broadly-written large-language model regarding healthy practices in raising children may offer up good advice gleaned from high-quality sources, but may also offer less-optimal advice or even “hallucinated” guidance that could be dangerous — and may not even be able to interpret context and nuance in the query or situation.
But a model that is built, from the ground up, to limit data sources to those which are reasonably reputable and have the ability to state when something is not known or that there is no consensus, would be likely to be both useful and safe — and may have a better chance of moving towards eventually incorporating context in queries. If anything, this is the approach taken by professionals whom parents generally find to be the most helpful when discussing parenting challenges. Ultimately, the goal is a system that works for us and advances the application and sharing of knowledge and innovation across civilization, rather than a constant struggle among data sources, which may or may not have any validity or even reality.
Ultimately, our real test-of-success may be to ask if any AI proposal, product, or service reasonably and reliably supports the health of human relationships, whether that be at the level of individuals, communities, or society as a whole.
Personal AI, Family Systems and the Social Ecology of Everyday Life
This above test-of-success for AI is important – and we must take it as a personal challenge. That is, we all, and human ecologists in particular, must pay special attention to generative personal AI. The tools that promise to support personal productivity, creativity, and assistance in daily tasks must be designed and used with great care, and informed by what we know and are constantly learning about healthy human development and social connection at the interpersonal scale. Here is where industry leaders, experts and scholars must battle with their own hubris and accept the fact that they are in uncharted waters. Research learning from lived experience, collaboration across differences, and working iteratively at an ethical scale is needed to get things right. How can we promote thriving and wellbeing in personal AI? Here we offer a few tentative operating instructions to help us navigate this unchartered territory.
Use AI to help people connect people constructively and reduce isolation - and refrain from use when it does not. As we consider impacts on human relationships and connection in family and community in all personal AI, explore how tools can be designed to sustain and support positive human connection.
Question conventional wisdom with research. Human ecologists, and leaders from all disciplines, must question our own assumptions and do the needed research to develop the much needed evidence-base for effective, ethical, human-centered AI.
Take a life-course perspective. From prenatal to elderhood, AI tools must support the developmental tasks of each life stage, and strengthen, not substitute for, human care. We anticipate that there are different recommended or helpful uses of AI at different points in the life course. What’s best for infants and toddlers? Teens? Adults? Elders? What is best in an educational context for pre-school, elementary, secondary and higher education? How can we be sure that AI is liberatory in relation to historical marginalization and oppression related to gender, ability, race, ethnicity, and all other dimensions of human diversity.
Implement AI innovations at a pace and scale that is informed by risks and benefits. Much of the conversation about AI relates to who will use it, who will have control over it, what we can and should do with it, and how we will make it accessible. However, it is important to also consider the pace and scale of change as matters of concern that require collective decision-making and policy guidance in themselves. As we know, a large motor vehicle on a highway can move people where they want to go, and carry what is needed to meet life-saving needs. But even if these elements are in place, that same vehicle poses harm if it is too big, goes too fast, or heads in the wrong direction.
First, do no harm. This medical aphorism is arguably a good starting point for any enterprise we undertake. And it is especially useful as a guiding principle for human-centered AI efforts. We may not be able to anticipate the harms of every AI tool, but we have a responsibility to crash-test our best ideas, and to take on the grim task of imagining the worst things that can happen, precisely so that we can prevent them.
These are not rules for technologists alone; they are a shared civic responsibility. To co-create AI for good, every household, school, and workplace becomes a site of ethical reflection — a place where we ask how technology shapes our shared ecosystem of meaning and care.
We offer these initial principles as the beginning of a conversation among human ecologists and beyond, in the hopes of working towards a transdisciplinary effort that allows us to optimize the impact of AI in our lives.
Creating AI together for a More Human World
Artificial Intelligence. Is it a contemporary Frankenstein’s creature that will change our lives according to his whim with unstoppable force? Is it artifice - a fake, a forgery, a knock off, a hollow simulation? Or is it a wonder of human creation, on a level similar to the harnessing of fire or electricity, or of writing, or space flight, an accomplishment that we should emphasize? Perhaps this technology is the creation of something that fills us with awe - a human achievement that offers a generative tool to tap the wisdom of the human hive? A tool that, if we use it well, can allow us to learn and do and play, and somehow become more connected, and more human.
Like any ecosystem, the digital world will evolve. Our task is to tend to it wisely, steward with responsibility, and guide with caution alongside our hopes and optimism, to ensure that AI only strengthens the webs of life, learning, and care that make us human. While we can’t predict the future we do feel certain about one thing: AI will be what we make it.
Artificial intelligence is in the world, and its existence confers upon us a frightening responsibility—and also a great opportunity. We call on human ecologists to action. Take your place in co-creating the future. Advance your work, and amplify your expertise. And we also call leaders and community members in all sectors and disciples – let's discover and work together with a human ecological mindset. Let’s get this right.
About the authors
Soyeon Shim, PhD, Elizabeth Holloway Schar Dean, School of Human Ecology, holds the Ted Kellner Bascom Professorship in Consumer Science, at the University of Wisconsin-Madison. Serving as dean since 2012, the School of Human Ecology has transformed under her leadership into a hub for interdisciplinary research, education, and outreach at the university, as well as nationally and globally. As a scholar of consumer and financial behavior, Shim has authored and co-authored more than 110 scholarly articles. She founded the longitudinal study APLUS to study young adults’ financial habits and life outcomes, findings which have informed the U.S. Presidential Council of Financial Capability for financial education and policy.
Dipesh Navsaria, MPH, MSLIS, MD is a pediatrician working in the public interest, blending the roles of physician, occasional children’s librarian, educator, public health professional and child health advocate. With graduate degrees in public health, children’s librarianship, physician assistant studies, and medicine, he brings unique interests and experiences together. A professor of Human Development and Family Studies at the School of Human Ecology, and of pediatrics at the School of Medicine and Public Health at the University of Wisconsin–Madison, he continues to practice outpatient pediatrics. He works regionally and nationally with Reach Out and Read and the American Academy of Pediatrics, and is the host of the award-winning Reach Out and Read Podcast.
Lori DiPrete Brown is the Director of Global Health and Human Ecology and a Distinguished Teaching Faculty at the UW-Madison School of Human Ecology. Her community-engaged teaching, outreach, and scholarship focus on human ecology as it relates to the health and well-being of women and children. Throughout her career, DiPrete Brown has had the privilege of collaborating with international leaders to strengthen health and social service programs in 19 countries around the world, including to the development of national quality improvement efforts in Chile and Ethiopia. From 2011-2016 she directed UW–Madison’s Quality Improvement Leadership Institute, which engaged more than 100 leaders from 24 countries. She is the author of Foundations for Global Health Practice (Wiley, 2018). She has served in the US Peace Corps in Honduras, and holds degrees from Yale College, the Harvard School of Public Health, and the Harvard Divinity School.