Patent Law Doesn’t Need To Recognize AI Inventors
Earlier this year, the U.S. Patent and Trademark Office rightly rejected two patent applications that named an AI system as the inventor, making clear its position to limit inventorship only to human beings, even when it is an AI system that is functionally inventing. The AI inventor at the heart of this case is DABUS, an AI system that mimics the neural patterns of the human mind to independently combine basic concepts into a complex idea that it can self-identify as original. Stephen Thaler, who created DABUS, listed the AI system as the inventor of two ideas; interlocking food containers that are easy for robots to grasp and a warning light that flashes in a rhythm that is hard to ignore. Thaler argues that the law should recognize DABUS, rather than him, as the inventor of these ideas because crediting a human with work they did not wholly invent devalues traditional human inventorship. But Thaler is wrong. The role of the patent system is to protect an inventor’s economic rights, not their moral rights.
5 Q’s for Yiannis Kiachopoulos, CEO of Causaly
The Center for Data Innovation spoke with Yiannis Kiachopoulos, co-founder and chief executive officer of Causaly, a research platform based in London that uses AI to mine and analyze scientific biomedical information. Kiachopoulos discussed how Causaly’s AI and natural language processing supports scientists by accelerating the research process, thereby enabling rapid innovation and progress in healthcare.
Can Algorithms Tackle the ‘Infodemic’?
The head of the World Health Organization declared in March that “we’re not just fighting an epidemic; we’re fighting an infodemic,” referring to the surge of false information about COVID-19 coming from nonexperts peddling fake cures to cybercriminals using hoaxes to steal money and data. The spread of inaccurate and deliberately false information is not new in the Internet age; it has plagued elections and grown during past times of crisis, but methods to tackle it have changed. Digital platforms, including search engines, social media sites, and e-commerce sites, have taken steps to remove false information and elevate authoritative content, using both automated and manual techniques. But critics argue we shouldn’t use algorithms to remove or label content because they are too often inaccurate or biased. Join the Center for Data Innovation for a video webinar on July 8, 2020, from 12:00 PM to 1:00 PM (EDT) to discuss the efficacy of using algorithms to moderate content, the role algorithms can play in addressing the infodemic, and the ways policymakers can support innovation in automated content moderation.
Is the EU’s AI Policy Headed in the Right Direction?
The European Commission is preparing a coordinated approach to developing and adopting AI. The Commission outlined initial policy options in its AI white paper, and after receiving public feedback will release a highly anticipated legislative proposal on AI in the first quarter of 2021. What feedback have stakeholders given, and which ideas do they believe the Commission will include in future legislation? Join the Center for Data Innovation for a video webinar on July 15, 2020, from 3:00 PM to 4:00 PM (CEST) to take stock of the perspectives of policymakers, experts, and industry representatives, and to assess the extent to which the EU AI white paper includes the right tools to strengthen EU competitiveness and innovation in the algorithmic economy.
Will the EU Data Strategy Prepare Europe to Lead in the Data Economy?
Data-driven innovation will be essential to EU competitiveness. To prepare for this future, the European Commission released a data strategy in February which proposes to create a single market for data to facilitate government-to-business, business-to-business, and business-to-government data sharing and roll out tools to give users more control over their data. The Commission has made clear that the EU’s approach to data should follow a “European way” but it has not yet specified what that will entail or how this approach will allow it to compete and trade with China and the United States. Feedback from the public consultation that recently ended will help inform a future EU legislative framework designed to overcome European challenges to realizing its potential in the data economy. Join the Center for Data Innovation for a video webinar on July 22, 2020, from 3:00 PM to 4:00 PM (CEST) to discuss how various stakeholders view these proposals, and to assess the extent to which the EU’s data strategy is on track to strengthen EU competitiveness and innovation.
European AI Policy Conference
AI is emerging as the most important technology in a new wave of digital innovation that is transforming industries around the world. Businesses in Europe are at the forefront of some of the latest advancements in the field, and European universities are home to the greatest concentration of AI researchers in the world. To fully realize its vision for AI, Europe needs an influx of resources and talent, plus some important policy changes. Join the Center for Data Innovation on December 1, 2020, in Brussels to discuss why European success in AI is important, how the EU compares to other world leaders today, and what steps European policymakers should take to be more competitive in AI.
- Detecting Low-Intensity Earthquakes
Researchers led by an individual from the California Institute of Technology have developed an AI-enabled system that has detected over 22,000 earthquakes, most of which were unknown to humans. The earthquakes ranged in magnitude from 0.7 to 4.4, and the software created one of the most detailed descriptions to date of earthquake swarms. These are strings of usually low-intensity earthquakes, and the system logged their time of occurrence and location.
2. Using AI to Document War Crimes
A group of organizations led by Swansea University in the UK is using machine learning to document war crimes in Yemen. The organizations trained a system to analyze images and videos to detect BLU-63, a type of illegal munition that sprays out smaller explosives upon impact. The system can identify the munition with over 90 percent accuracy.
3. Advancing Quantum Computing
Honeywell, a company known for developing control systems for buildings and aircrafts, claims to have built the world’s highest-performing quantum computer. Honeywell measured its computer’s capabilities using quantum volume, a metric IBM created that uses a computer’s number of qubits, error rate, and how long the system can make calculations before the qubits stop working.
4. Analyzing the Merger of Black Holes
Researchers led by an individual from the California Institute of Technology have combined gravitational wave data and data from a robotic camera to find evidence that merging black holes could lead to an explosion of light. Gravitational wave data from May 21, 2019, indicates that black holes were spiraling toward each other. The researchers analyzed sky surveys, finding that a flare of light developed and faded in the same area and time as the merger of the black holes.
5. Creating an AI Virtual Patient
GNS Healthcare, a data analytics firm based in Massachusetts, has created a platform that uses AI to simulate how patients with a blood cancer called multiple myeloma might respond to different treatments. The firm built the platform using a dataset with information on the gene expressions, protein measurements, and attempted therapies of more than 1,000 patients. Drugmakers can use the platform to determine which patients to recruit for clinical trials.
6. Developing an AI Bedside Monitor
The U.S. Food and Drug Administration has approved a bedside device from Circadia Health, a startup based in the United Kingdom, that uses AI to monitor respiratory health. The device detects a person’s breathing and chest movement using radar and sound, and algorithms can analyze the data to identify the early signs of COVID-19, such as breathlessness.
7. Deciphering Coronavirus Research
Primer AI, a startup based in San Francisco, has developed a public dashboard that highlights the latest research trends, news coverage, and social media discussion about coronavirus research. The platform uses natural language processing to analyze the more than 27,000 papers researchers have published about coronavirus to discover trends and write summaries. Individuals can use the platform to learn which papers are generating the most discussion and can sort the papers by categories, such as “forecasting and modeling.”
8. Linking Gene Mutations to Living Longer
Researchers from the University of Utah and the University of Louisville have analyzed the genetic material of three generations of individuals from 41 families to determine that developing fewer mutations is linked to living longer. The researchers found that individuals in the bottom 25 percent for the number of mutations outlived individuals in the top 75 percent by five years.
9. Linking a Volcanic Eruption to the Collapse of the Roman Empire
Researchers led by an individual from the Desert Research Institute in Nevada have used an array of sensors to determine that a volcanic eruption in Alaska may have helped spur the collapse of the Roman Empire. The researchers analyzed ice cores that corresponded to 43 BCE, and sensors found evidence of sulfur and volcanic ash. This evidence matched samples from a large volcanic eruption in Alaska, which could have caused substantial rain and the temperature to drop substaintially in the Mediterranean. Such conditions match accounts from Roman writers who noted that famines were occurring at the time.
10. Building the World’s Fastest Supercomputer
Fugaku, a Japanese supercomputer, is now the fastest in the world. Riken and Fujitsu developed the computer, which is 2.8 times as fast as the previous record-holder, the United States’ Summit. Researchers have been using Fugaku to research coronavirus and simulate its spread.
Data Visualization of the Week
Visualizing the Plight of Russian Orphans
Russian investigative news site I-Stories has created several data visualizations highlighting the plight of Russian orphans. Russia banned U.S. citizens from adopting Russians in 2013, and a chart shows that the percentage of Russian orphans families adopted has declined since the ban. Another graph shows that the rate of guardians returning children to orphanages has increased.
Dataset of the Week
Identifying Aircraft in Satellite Imagery
In-Q-Tel, a U.S. government-funded venture capital firm, and AI.Reverie, a startup based in New York that creates synthetic data to train machine learning algorithms, have released a dataset of satellite imagery. The duo released the dataset, which combines 250 real satellite images and more than 50,000 synthetic images, to advance the development of computer vision systems that can detect aircraft. The images contain numerous labels, such as an aircraft’s length, wingspan, and number of engines.