U.S. AI Summer Camps

2021 ◽  
Author(s):  
Claire Perkins ◽  
Kayla Goode
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Summer Camp ◽  
The United States ◽  
Summer Camps ◽  
Intelligence Education

Summer camps are an integral part of many U.S. students’ education, but little is known about camps that focus on artificial intelligence education. This data brief maps out the AI summer camp landscape in the United States and explores the camps’ locations, target age ranges, price, and hosting organization type.

scholarly journals Medical Record Keeping in the Summer Camp Setting

2016 ◽  
Vol 07 (04) ◽  
pp. 1154-1167
Author(s):  
Jaycelyn Holland ◽  
Stuart Weinberg ◽  
S. Rosenbloom ◽  
Laura Kaufman
Keyword(s):  
Medical Record ◽  
Summer Camp ◽  
The United States ◽  
Summer Camps ◽  
Pediatric Care ◽  
Health Staff ◽  
Health Providers ◽  
Health Records ◽  
Record Keeping ◽  
Survey Responses

Summary Background Approximately one fifth of school-aged children spend a significant portion of their year at residential summer camp, and a growing number have chronic medical conditions. Camp health records are essential for safe, efficient care and for transitions between camp and home providers, yet little research exists regarding these systems. Objective To survey residential summer camps for children to determine how camps create, store, and use camper health records. To raise awareness in the informatics community of the issues experienced by health providers working in a special pediatric care setting. Methods We designed a web-based electronic survey concerning medical recordkeeping and healthcare practices at summer camps. 953 camps accredited by the American Camp Association received the survey. Responses were consolidated and evaluated for trends and conclusions. Results Of 953 camps contacted, 298 (31%) responded to the survey. Among respondents, 49.3% stated that there was no computer available at the health center, and 14.8% of camps stated that there was not any computer available to health staff at all. 41.1% of camps stated that internet access was not available. The most common complaints concerning recordkeeping practices were time burden, adequate completion, and consistency. Conclusions Summer camps in the United States make efforts to appropriately document healthcare given to campers, but inconsistency and inefficiency may be barriers to staff productivity, staff satisfaction, and quality of care. Survey responses suggest that the current methods used by camps to document healthcare cause limitations in consistency, efficiency, and communications between providers, camp staff, and parents. As of 2012, survey respondents articulated need for a standard software to document summer camp healthcare practices that accounts for camp-specific needs. Improvement may be achieved if documentation software offers the networking capability, simplicity, pediatrics-specific features, and avoidance of technical jargon. Citation: Kaufman L, Holland J, Weinberg S, Rosenbloom ST. Medical record keeping in the summer camp setting.

The ideological divide in public perceptions of self-driving cars

2020 ◽  
Vol 29 (4) ◽  
pp. 436-451
Author(s):  
Yilang Peng
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Scientific Literacy ◽  
Autonomous Vehicles ◽  
The United States ◽  
Public Perceptions ◽  
New Information ◽  
Nationally Representative ◽  
Self Driving Cars ◽  
Social Conservatism

Applications in artificial intelligence such as self-driving cars may profoundly transform our society, yet emerging technologies are frequently faced with suspicion or even hostility. Meanwhile, public opinions about scientific issues are increasingly polarized along the ideological line. By analyzing a nationally representative panel in the United States, we reveal an emerging ideological divide in public reactions to self-driving cars. Compared with liberals and Democrats, conservatives and Republicans express more concern about autonomous vehicles and more support for restrictively regulating autonomous vehicles. This ideological gap is largely driven by social conservatism. Moreover, both familiarity with driverless vehicles and scientific literacy reduce respondents’ concerns over driverless vehicles and support for regulation policies. Still, the effects of familiarity and scientific literacy are weaker among social conservatives, indicating that people may assimilate new information in a biased manner that promotes their worldviews.

scholarly journals Rising Sino-U.S. Competition in Artificial Intelligence

2018 ◽  
Vol 04 (02) ◽  
pp. 241-258 ◽  
Author(s):  
You Wang ◽  
Dingding Chen
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
The United States ◽  
Cutting Edge ◽  
The Other ◽  
Strategic Competition ◽  
Bilateral Relations ◽  
The Future ◽  
Important Field ◽  
Political Security

Both China and the United States are international leaders in artificial intelligence (AI). Although there remains a significant gap between them in cutting-edge technologies, and they have adopted different methods of planning and implementation, both countries have been mobilizing national resources and formulating policies to promote AI development, so as to achieve a strategic advantage over the other, especially against the backdrop of ever more intense and complicated strategic competition between them in recent years. As an epitome of their changing relationship, Sino-U.S. competition in AI development is manifested in economic, political, security, technological and other fields. It is expected that artificial intelligence will become an even more important field of competition between China and the United States, and that the trends of AI development and competition will to some extent determine the future dynamics of their bilateral relations.

scholarly journals China’s AI experience: industrial digitalization

2020 ◽  
Vol 28 (3) ◽  
pp. 536-546
Author(s):  
Marina S. Reshetnikova
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Global Economy ◽  
The United States ◽  
High Tech ◽  
Global Innovation ◽  
Innovative Products ◽  
Fundamental Research ◽  
The Moment

The rapid acceleration of scientific and technological progress, which started at the beginning of the 21st century, has become a decisive factor in influencing the global economy. Who will lead the global innovation race? This problem is especially relevant in the field of artificial intelligence (AI). At the moment, the United States and China are the main participants in the battle for dominance in this area. The author assesses Chinas innovative potential in the field of AI and identifies its achievements in this area. Based on the statistics provided, Chinas AI leadership has reached a critical point. China is confidently leading the new fundamental research of artificial intelligence, forming its theoretical base and applied research and development, which will contribute to the creation of new high-tech innovative products and services. However, in terms of the number and quality of AI specialists (AI Talents) and the number of companies engaged in AI, China is still lagging behind its main rival, namely the United States. The author proved that, despite the obvious successes of China, the United States still has an equal lead in the global innovation race.

ARTIFICIAL INTELLIGENCE IN THE UNITED STATES

2022 ◽  
pp. 5-12
Author(s):  
Margaret A. Goralski ◽  
Krystyna Górniak-Kocikowska
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
The United States

Conclusion

2020 ◽  
pp. 97-102
Author(s):  
Benjamin Wiggins
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Machine Learning ◽  
Risk Assessment ◽  
Big Data ◽  
The United States ◽  
Blaise Pascal ◽  
Division Problem ◽  
The World

Can risk assessment be made fair? The conclusion of Calculating Race returns to actuarial science’s foundations in probability. The roots of probability rest in a pair of problems posed to Blaise Pascal and Pierre de Fermat in the summer of 1654: “the Dice Problem” and “the Division Problem.” From their very foundation, the mathematics of probability offered the potential not only to be used to gain an advantage (as in the case of the Dice Problem), but also to divide material fairly (as in the case of the Division Problem). As the United States and the world enter an age driven by Big Data, algorithms, artificial intelligence, and machine learning and characterized by an actuarialization of everything, we must remember that risk assessment need not be put to use for individual, corporate, or government advantage but, rather, that it has always been capable of guiding how to distribute risk equitably instead.

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