Julia Rosa Reis is the founder and CEO of ShootShare. Her work explores who gets to shape technology, how it changes creative work and what we mean by intelligence.
What are the biggest opportunities for women in your sector of the digital industry right now?
To define what technological progress is for.
Every optimisation begins with a decision about what matters. We choose the objective, the boundaries of the problem and the costs we count. A process can appear more efficient because somebody else’s unpaid work has disappeared from the calculation. Those choices deserve as much scrutiny as the technology implementing them.
I see an opportunity for us to have greater authorship over these foundations: the research questions, business models and technical systems through which value is created and distributed.
The design of an interface helps determine what people can understand and influence. I see those decisions as part of the responsibility of building technology.
I am interested in systems that connect distributed expertise. Local professionals bring knowledge of a place, its working relationships and its creative possibilities. Digital infrastructure can connect that expertise to international demand while allowing it to shape the work. Global production should create economic value for the people and places involved. That gives a practical direction to the technology we build. I am particularly interested in the relationship between synthetic media and documented reality. AI expands our capacity to generate possibilities.
There is also value in establishing how something was made, who participated and what claims it can support. I see an opportunity to make real-world creative production scalable while preserving that context. That connects digital infrastructure with authorship, consent and the local participation of experts. The conditions under which something comes into existence are part of its value.
I think we need greater precision about visual plausibility, originality and evidence. A representation can be compelling for many reasons. When it is offered as evidence, its origin, the interventions made to it and the limits of the claim become essential. For me, this is a question of epistemic responsibility: being clear about the grounds on which we ask someone to believe something.
AI makes the question of purpose more consequential. I take its capacity to generate original work seriously. I want us to be equally rigorous about how the benefits are distributed, whose contribution is recognised and what conditions we create for people to participate.
What are some of the challenges that you still see for women in the industry?
One challenge is securing the authority to define the problem in the first place.
The people selecting a system’s objectives have considerable influence over what it will recognise as success. We need meaningful authority at that stage: deciding what gets built, which evidence informs it and whose experience changes the specification.
That authority also requires economic conditions that make participation sustainable. Fair remuneration, clear rights and dependable payment affect who can afford to remain in an industry and develop expertise. Being able to build an independent career, understand the terms of work and negotiate them is a practical form of agency. Those conditions belong in the design of digital business models.
Representation also has an economic dimension. I want claims of inclusion and fairness to be examined through access to paid work, authorship and decision-making, alongside what appears on screen. In digital media, it is increasingly possible to depict almost any identity. That makes it important to be explicit about how the people and communities being represented participate in creating and benefiting from the work.
I am particularly concerned about existing inequalities becoming embedded in automated decisions. AI systems can reproduce biases arising from institutions and human judgement, alongside those in data and computation. Once embedded in a deployed system, those assumptions can influence access to opportunities at scale.
This is where my research becomes practical: making assumptions visible, examining the adequacy of our categories and remaining accountable to evidence. For me, progress means having the resources and authority to question a system’s premises and to build and test alternatives.
What support structures and organisations are most important and effective to you as a woman in the digital industry?
I value support that combines intellectual seriousness with practical commitment.
That means people willing to examine an idea carefully, challenge its assumptions and help create the conditions in which it can be tested. Honest criticism, technical knowledge, access to decision-makers and paid opportunities all matter.
My work crosses creative production, technology, business and cultural philosophy, so I value communities where knowledge can move between disciplines. The person who understands a system’s human consequences and the person who understands its technical architecture should be able to influence each other’s thinking. Shared commitments to fairness, transparency and reliability have supported our collaborative approach since ShootShare’s beginnings. I value relationships in which those principles become dependable working conditions.
These relationships also shape how people collaborate, whose ideas are developed and who can act on them. That matters because creative work, in turn, influences how people see and understand the world.
Alongside my work in technology, I serve as Director of Corporate Alliances and Brand Strategy for Exploration Film Festival Davos, which supports field sciences. Here I see a role for cultural institutions in bringing scientific inquiry, technology and public understanding into conversation. Contributing to those connections is one way I put my belief into practice.
Support becomes effective through active contribution to a shared goal. Time, trusted relationships, knowledge and resources give us the capacity to act on an idea. I judge a support structure by how effectively it creates those conditions and how widely it makes them available.
What is the biggest misconception (a) about women in the digital industry, and (b) by women in the digital industry?
(a) That our principal contribution to technology is a particular set of skills: empathy, care or communication.
We contribute across the full intellectual scope of the field: originating ideas, constructing theories, designing systems and making consequential commercial decisions. Defining the purpose of a technology and understanding its effects are themselves demanding forms of expertise.
My route into technology grew out of practical experience of designing systems. Building ShootShare meant translating that experience into decisions about information, coordination and responsibility. I see deep knowledge of a field as a source of technical insight: it helps you identify the problem, recognise dependencies and judge whether a proposed system works in practice.
I want us to be recognised as authors of the systems through which we live and work.
(b) One assumption I would encourage us to question is that credibility requires accepting a field’s established definition of success.
Terms such as intelligence, productivity, creativity and growth contain assumptions that deserve examination. A measure of productivity can reward greater output while overlooking who absorbs the additional work. A growth target can leave the distribution of its benefits unexamined.
How we define completion affects what we take responsibility for. For me, a production’s value includes considering the resources it requires, its labour conditions and the useful life of what remains afterwards. Those consequences should be considered when the process is designed and costed.
Developing expertise includes learning to distinguish an evidence-based constraint from a convention, an incentive or a choice. Ultimately, it is about the ethical standards we hold ourselves to.
What one piece of advice would you offer a woman starting in the digital industry today?
Learn to examine the premises and understand how a system works, how its goals were chosen and what evidence supports its claims. Then make your own assumptions explicit, test them and remain willing to revise them.
That is the combination I value: intellectual independence and responsibility for consequences. It gives you a basis for deciding what deserves your effort, what needs to change and what you are prepared to build. Moving between disciplines helps us to recognise assumptions. In a recent thought experiment about artificial intelligence, I explored how our conclusions change with the definition of life we adopt. That required distinguishing a system’s origin, its dependence on infrastructure and the properties it possesses. Separating those questions helps clarify what an argument establishes and what still requires evidence.
I find that discipline valuable whenever a familiar category begins to shape our understanding of something new. Be precise about the future your work makes possible.
