Stefaan Verhulst

Saahil Jayraj Dama at JoDS: “Today too many people are still deprived of basic amenities such as medicine, while current patent laws continue to convolute and impede innovation. But if allowed, AI can provide an opportunity to redefine this paradigm and be the catalyst for change—if….

Which brings us to the most befitting answer: No one owns the intellectual property rights to AI-generated creations, and these creations fall into the public domain. This may seem unpalatable at first, especially since intellectual property laws have played such a fundamental role in our society so far. We have been conditioned to a point where it seems almost unimaginable that some creations should directly enter the public domain upon their birth.

But, doctrinally, this is the only proposition that stays consistent to extant intellectual property laws. Works created by AI have no rightful owner because the application of mind to generate the creation, along with the actual generation of the creation, would entirely be done by the AI system. Human involvement is ancillary and is limited to creating an environment within which such a creation can take form.

This can be better understood through a hypothetical example: If an AI system were to invent a groundbreaking pharmaceutical ingredient which completely treats balding, then the system would likely begin by understanding the problem and state of prior art. It would undertake research on causes of balding, existing cures, problems with existing cures, and whether its proposed cure would have any harmful side effects. It would also possibly combine research and knowledge across various domains, which could range from Ayurveda to modern-day biochemistry, before developing its invention.

The developer can lay as much stake to this invention as the team behind AlphaGo for beating Lee Sedol at Go. The user is even further detached from the exercise of ingenuity: She would be the person who first thought, “We should build a Go playing AI system,” and direct the AI system to learn Go by watching certain videos and playing against itself. Despite the intervention of all these entities, the fact remains that the victory only belongs to AlphaGo itself.

Doctrinal issues aside, this solution ties in with what people need from intellectual property laws: more openness and accessibility. The demands for improved access to medicines and knowledge, fights against cultural monopolies, and brazen violations of unjust intellectual property laws are all symptomatic of the growing public discontent against strong intellectual property laws. Through AI, we can design legal systems which address these concerns and reform the heavy handed approach that has been adopted toward intellectual property rights so far.

Tying the Threads Together

For the above to materialize, governments and legislators need to accept that our present intellectual property system is broken and inconsistent with what people want. Too many people are being deprived of basic amenities such as medicines, patent trolls and patent thickets are slowing innovation, educational material is still outside the reach of most people, and culture is not spreading as widely as it should. AI can provide an opportunity for us to redefine this paradigm—it can lead to a society that draws and benefits from an enriched public domain.

However, this approach does come with built-in cynicism because it contemplates an almost complete overhaul of the system. One could argue that if open access for AI-generated creations does become the norm, then innovation and creativity would suffer as people would no longer have the incentive to create. People may even refuse to use their AI systems, and instead stick to producing inventions and creative works by themselves. This would be detrimental to scientific and cultural progress and would also slow adoption of AI systems in society.

Yet, judging by the pace at which these systems have progressed so far and what they can currently do, it is easy to imagine a reality where humans developing inventions and producing creative works almost becomes an afterthought. If a machine can access all the world’s publicly available knowledge and information to develop an invention, or study a user’s likes and dislikes while producing a new musical composition, it is easy to see how humans would, eventually, be pushed out of the loop. AI-generated creations are, thus, inevitable.

The incentive theory will have to be reimagined, too. Constant innovation coupled with market forces will change the system from “incentive-to-create” to “incentive-to-create-well.” While every book, movie, song, and invention is treated at par under the law, only the best inventions and creative works will thrive under the new model. If a particular developer’s AI system can write incredible dialogue for a comedy film or invent the most efficient car engines, the market would want more of these AI systems. Thus incentive will not be eliminated, it will just take a different form.

It is true that writing about such grand schemes is significantly tougher than practically implementing them. But, for any idea to succeed, it must start with a discussion such as this one. Admittedly, we are still a moonshot away from any country granting formal recognition to open access as the basis of its intellectual property laws. And even if a country were to do this, it faces a plethora of hoops to jump through, such as conducting feasibility-testing and dealing with international and internal pressure. Despite these issues, facilitating better access through AI systems remains an objective worth achieving for any society that takes pride in being democratic and equal….(More)”.

Blog Post by Jason Farra: “When it came to gathering input for their new Environmental Master Plan, the Town of Okotoks, AB decided to try something different. Rather than using more traditional methods of consulting residents, they turned to a Canadian civic tech company called Ethelo.

Ethelo’s online software “enables groups to evaluate scenarios, apply constraints, prioritize options and come up with decisions that will get broad support from the group,” says John Richardson, the company’s CEO and founder.

Okotoks gathered over 350 responses, with residents able to compare and evaluate different solutions for a variety of environmental issues, including what kind of transportation and renewable energy options they wanted to see in their town.

“Ethelo offered a different opportunity in terms of allowing a conversation to happen online,” Marni Hutchison, Communications Specialist with the Town of Okotoks, said in a case study of the project. “We can see the general consensus as it’s forming and participants have more opportunities to see different perspectives.”

John sees this as part of a broader shift in how governments and other organizations are approaching stakeholder engagement, particularly with groups like IAP2 working to improve engagement practices by training practitioners.

Rather than simply consulting, then informing residents about decisions, civic tech startups like Ethelo allow governments to involve residents more actively in the actual decision-making process….(More)”.

Blog post by Andrew Burgess: “Something curious is happening in Finland. Though much of the global debate around artificial intelligence (A.I.) has become concerned with unaccountable, proprietary systems that could control our lives, the Finnish government has instead decided to embrace the opportunity by rolling out a nationwide educational campaign.

Conceived in 2017, shortly after Finland’s A.I. strategy was announced, the government wants to rebuild the country’s economy around the high-end opportunities of artificial intelligence, and has launched a national programto train 1 percent of the population — that’s 55,000 people — in the basics of A.I. “We’ll never have so much money that we will be the leader of artificial intelligence,” said economic minister Mika Lintilä at the launch. “But how we use it — that’s something different.”

Artificial intelligence can have many positive applications, from being trained to identify cancerous cells in biopsy screenings, predict weather patterns that can help farmers increase their crop yields, and improve traffic efficiency.

But some believe that A.I. expertise is currently too concentrated in the hands of just a few companies with opaque business models, meaning resources are being diverted away from projects that could be more socially, rather than commercially, beneficial. Finland’s approach of making A.I. accessible and understandable to its citizens is part of a broader movement of people who want to democratize the technology, putting utility and opportunity ahead of profit.

This shift toward “democratic A.I.” has three main principles: that all society will be impacted by A.I. and therefore its creators have a responsibility to build open, fair, and explainable A.I. services; that A.I. should be used for social benefit and not just for private profit; and that because A.I. learns from vast quantities of data, the citizens who create that data — about their shopping habits, health records, or transport needs — have a right to say and understand how it is used.

A growing movement across industry and academia believes that A.I. needs to be treated like any other “public awareness” program — just like the scheme rolled out in Finland….(More)”.

Paper by Dennis Hummel and Alexander Maedche: “Changes in the choice architecture, so-called nudges, have been employed in a variety of contexts to alter people’s behavior. Although nudging has gained a widespread popularity, the effect sizes of its influences vary considerably across studies. In addition, nudges have proven to be ineffective or even backfire in selected studies which raises the question whether, and under which conditions, nudges are effective. Therefore, we conduct a quantitative review on nudging with 100 primary publications including 317 effect sizes from different research areas. We derive four key results. (1) A morphological box on nudging based on eight dimensions, (2) an assessment of the effectiveness of different nudging interventions, (3) a categorization of the relative importance of the application context and the nudge category, and (4) a comparison of nudging and digital nudging. Thereby, we shed light on the (in)effectiveness of nudging and we show how the findings of the past can be used for future research. Practitioners, especially government officials, can use the results to review and adjust their policy making….(More)”.

Paper by Elizabeth Ford et al in Learning Health Systems: “The last six years have seen sustained investment in health data science in the UK and beyond, which should result in a data science community that is inclusive of all stakeholders, working together to use data to benefit society through the improvement of public health and wellbeing.

However, opportunities made possible through the innovative use of data are still not being fully realised, resulting in research inefficiencies and avoidable health harms. In this paper we identify the most important barriers to achieving higher productivity in health data science. We then draw on previous research, domain expertise, and theory, to outline how to go about overcoming these barriers, applying our core values of inclusivity and transparency.

We believe a step-change can be achieved through meaningful stakeholder involvement at every stage of research planning, design and execution; team-based data science; as well as harnessing novel and secure data technologies. Applying these values to health data science will safeguard a social license for health data research, and ensure transparent and secure data usage for public benefit….(More)”.

Paper by Serge Abiteboul and Julia Stoyanovich: “The data revolution continues to transform every sector of science, industry and government. Due to the incredible impact of data-driven technology on society, we are becoming increasingly aware of the imperative to use data and algorithms responsibly — in accordance with laws and ethical norms. In this article we discuss three recent regulatory frameworks: the European Union’s General Data Protection Regulation (GDPR), the New York City Automated Decisions Systems (ADS) Law, and the Net Neutrality principle, that aim to protect the rights of individuals who are impacted by data collection and analysis. These frameworks are prominent examples of a global trend: Governments are starting to recognize the need to regulate data-driven algorithmic technology. 

Our goal in this paper is to bring these regulatory frameworks to the attention of the data management community, and to underscore the technical challenges they raise and which we, as a community, are well-equipped to address. The main .take-away of this article is that legal and ethical norms cannot be incorporated into data-driven systems as an afterthought. Rather, we must think in terms of responsibility by design, viewing it as a systems requirement….(More)”

Paper by Kathleen Elliott Vinson and Samantha A. Moppett: “…While individuals have the constitutional right to legal assistance in criminal cases, the same does not hold true for civil matters. Low-income Americans are unable to gain access to meaningful help for basic legal needs. Although legal aid organizations exist to help low-income Americans who cannot afford legal representation, the resources available are insufficient to meet current civil legal needs. Studies show more than 80 percent of the legal needs of low-income Americans go unaddressed every year. 

This article examines how law students, law schools, the legal profession, legal services’ agencies, and low-income individuals who need assistance, all have a shared interest—access to justice—and can work together to reach the elusive goal in the Pledge of Allegiance of “justice for all.” It illustrates how their collaborative leveraging of technology in innovative ways like digital pro bono services, is one way to provide access to justice. It discusses ABA Free Legal Answers Online, the program that the ABA pioneered to help confront the justice gap in the United States. The program provides a “virtual legal advice clinic” where attorneys answer civil legal questions that low-income residents post on free, secure, and confidential state-specific websites. The article provides a helpful resource of how law schools can leverage this technology to increase access to justice for low-income communities while providing pro bono opportunities for attorneys and students in their state…(More)”.

BBVA API Market: “How do town-planning decisions affect a city’s routines? How can data help assess and make decisions? The granularity and detailed information offered by PayStats allowed Madrid’s city council to draw a more accurate map of consumer behavior and gain an objective measurement of the impact of the traffic restriction measures on commercial activity.

In this case, 20 million aggregate and anonymized transactions with BBVA cards and any other card at BBVA POS terminals were analyzed to study the effect of the changes made by Madrid’s city council to road access to the city center.

The BBVA PayStats API is targeted at all kinds of organizations including the public sector, as in this case. Madrid’s city council used it to find out how restricting car access to Madrid Central impacted Christmas shopping. From information gathered between December 1 2018 and January 7 2019, a comparison was made between data from the last two Christmases as well as the increased revenue in Madrid Central (Gran Vía and five subareas) vs. the increase in the entire city.

According to the report drawn up by council experts, 5.984 billion euros were spent across the city. The sample shows a 3.3% increase in spending in Madrid when compared to the same time the previous year; this goes up to 9.5% in Gran Vía and reaches 8.6% in the central area….(More)”.

Article by Eduardo Alejandro Martínez Ceseña, Joseph Mutale, Mathaios Panteli, and Pierluigi Mancarella in The Conversation: “Access to reliable and affordable electricity brings many benefits. It supports the growth of small businesses, allows students to study at night and protects health by offering an alternative cooking fuel to coal or wood.

Great efforts have been made to increase electrification in Africa, but rates remain low. In sub-Saharan Africa only 42% of urban areas have access to electricity, just 22% in rural areas.

This is mainly because there’s not enough sustained investment in electricity infrastructure, many systems can’t reliably support energy consumption or the price of electricity is too high.

Innovation is often seen as the way forward. For instance, cheaper and cleaner technologies, like solar storage systems deployed through mini grids, can offer a more affordable and reliable option. But, on their own, these solutions aren’t enough.

To design the best systems, planners must know where on- or off-grid systems should be placed, how big they need to be and what type of energy should be used for the most effective impact.

The problem is reliable data – like village size and energy demand – needed for rural energy planning is scarce or non-existent. Some can be estimated from records of human activities – like farming or access to schools and hospitals – which can show energy needs. But many developing countries have to rely on human activity data from incomplete and poorly maintained national census. This leads to inefficient planning.

In our research we found that data from mobile phones offer a solution. They provide a new source of information about what people are doing and where they’re located.

In sub-Saharan Africa, there are more people with mobile phones than access to electricity, as people are willing to commute to get a signal and/or charge their phones.

This means that there’s an abundance of data – that’s constantly updated and available even in areas that haven’t been electrified – that could be used to optimise electrification planning….

We were able to use mobile data to develop a countrywide electrification strategy for Senegal. Although Senegal has one of the highest access to electricity rates in sub-Saharan Africa, just 38% of people in rural areas have access.

By using mobile data we were able to identify the approximate size of rural villages and access to education and health facilities. This information was then used to size and cost different electrification options and select the most economic one for each zone – whether villages should be connected to the grids, or where off-grid systems – like solar battery systems – were a better option.

To collect the data we randomly selected mobile phone data from 450,000 users from Senegal’s main telecomms provider, Sonatel, to understand exactly how information from mobile phones could be used. This includes the location of user and the characteristics of the place they live….(More)”

Paper by Chris Reed and Irene YH Ng: “This paper is a response to the Singapore Personal Data Protection Commission consultation on a draft AI Governance Framework. It analyses the five data trust models proposed by the UK Open Data Institute and identifies that only the contractual and corporate models are likely to be legally suitable for achieving the aims of a data trust.

The paper further explains how data trusts might be used as in the governance of AI, and investigates the barriers which Singapore’s data protection law presents to the use of data trusts and how those barriers might be overcome. Its conclusion is that a mixed contractual/corporate model, with an element of regulatory oversight and audit to ensure consumer confidence that data is being used appropriately, could produce a useful AI governance tool…(More)”.