Collaborating Authors


Autonomous vehicles are a dream for drug smugglers


Level 5 autonomous vehicles (AVs) will allow shipping companies to significantly decrease their costs and their liability as they will no longer need long-haul truck drivers. However, this also applies to smugglers. Trafficking of drugs, people, weapons, and black market goods will all receive a boon from AVs. There will be a massive increase in vehicles on the road with the advent of fully-autonomous technology. Long-haul delivery vehicles could largely become operated with no passengers inside, and will likely not even have a place for a passenger.

Toward a Rational and Ethical Sociotechnical System of Autonomous Vehicles: A Novel Application of Multi-Criteria Decision Analysis Artificial Intelligence

The expansion of artificial intelligence (AI) and autonomous systems has shown the potential to generate enormous social good while also raising serious ethical and safety concerns. AI technology is increasingly adopted in transportation. A survey of various in-vehicle technologies found that approximately 64% of the respondents used a smartphone application to assist with their travel. The top-used applications were navigation and real-time traffic information systems. Among those who used smartphones during their commutes, the top-used applications were navigation and entertainment. There is a pressing need to address relevant social concerns to allow for the development of systems of intelligent agents that are informed and cognizant of ethical standards. Doing so will facilitate the responsible integration of these systems in society. To this end, we have applied Multi-Criteria Decision Analysis (MCDA) to develop a formal Multi-Attribute Impact Assessment (MAIA) questionnaire for examining the social and ethical issues associated with the uptake of AI. We have focused on the domain of autonomous vehicles (AVs) because of their imminent expansion. However, AVs could serve as a stand-in for any domain where intelligent, autonomous agents interact with humans, either on an individual level (e.g., pedestrians, passengers) or a societal level.

Assured Autonomy: Path Toward Living With Autonomous Systems We Can Trust Artificial Intelligence

The challenge of establishing assurance in autonomy is rapidly attracting increasing interest in the industry, government, and academia. Autonomy is a broad and expansive capability that enables systems to behave without direct control by a human operator. To that end, it is expected to be present in a wide variety of systems and applications. A vast range of industrial sectors, including (but by no means limited to) defense, mobility, health care, manufacturing, and civilian infrastructure, are embracing the opportunities in autonomy yet face the similar barriers toward establishing the necessary level of assurance sooner or later. Numerous government agencies are poised to tackle the challenges in assured autonomy. Given the already immense interest and investment in autonomy, a series of workshops on Assured Autonomy was convened to facilitate dialogs and increase awareness among the stakeholders in the academia, industry, and government. This series of three workshops aimed to help create a unified understanding of the goals for assured autonomy, the research trends and needs, and a strategy that will facilitate sustained progress in autonomy. The first workshop, held in October 2019, focused on current and anticipated challenges and problems in assuring autonomous systems within and across applications and sectors. The second workshop held in February 2020, focused on existing capabilities, current research, and research trends that could address the challenges and problems identified in workshop. The third event was dedicated to a discussion of a draft of the major findings from the previous two workshops and the recommendations.

Tackling Climate Change with Machine Learning Artificial Intelligence

Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help. Here we describe how machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, we identify high impact problems where existing gaps can be filled by machine learning, in collaboration with other fields. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the machine learning community to join the global effort against climate change.

USPTO Issued Drone Delivery Patent To HorseFly – DEEP AERO DRONES – Medium


The latest drone-related patent has been awarded by the United States Patent and Trademark Office (USPTO) to the HorseFly Truck Launched Drone Package Delivery System from the Workhorse Group. Numbers of companies are coming forward and getting on board and the drone delivery patents that have been awarded is going up as well. "We feel that the patented HorseFly truck launched drone package delivery system is the first major change to the last mile delivery process since the invention of the package delivery truck. Drivers appreciate the fact that the HorseFly system is fast, reliable, and efficient and last mile package delivery is changing, and the HorseFly delivery system is leading the way," said Steve Burns, Workhorse CEO. Studies have shown that last-mile drone delivery can be both more-efficient and greener than deliveries via truck.

Would Delivery Drones Be All That Efficient? Depends Where You Live


If the idea of swarms of delivery drones dropping packages all over our cities started out as a joke, for some reason the punchline hasn't landed yet. Amazon applied for a patent in 2015 for a command center, like a beehive, plopped into your city, which isn't a worrying metaphor at all. Google has its own program in the works, which at least for the moment involves delivering burritos. Again, if this is a joke, it's got a very long fuse.

The 48 startups that launched at Y Combinator S16 Demo Day 2


The world's most prestigious startup school launched 48 companies today at part 2 of its Summer 2016 Demo Day. Nanoparticle analytics and delivery robots were amongst the products revealed in the B2B, biotech, enterprise, edtech, fintech, and hardware verticals. You can check out our write-ups of all 44 startups that launched yesterday, and TechCrunch's picks for the top 7 from the batch. Trying to distill trends from the hodgepodge of startups at Demo day can be futile, because the real winners are the ones ahead of the trends. For example, TechCrunch thought Airware's drone operating system was a little too early in 2013. It turned out to be smartly ahead of the curve. Now you see lots of drone startups in YC, but many are chasing Airware which has gone on to raise 70 million. Y Combinator president Sam Altman explains "The best company at any given Demo Day is not the one that fits the theme of that Demo Day. Altman cites the Alan Kay quote that "the best way to predict the future is to invent it", adding "I think short of that, the future is basically unknowable. What I like about YC is the companies get to invent the future. They don't have to guess." One important development is that 30% of this batch's companies were founded outside the US, a bigger portion than in the past. YC partner Justin Kan credits that to the program being around long enough that it's funded successful companies from tons of countries.