Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A 1______in educational content from online courses and the contemporary renaissance in AI seem to provide the conditions 2______to deliver personalized learning at scale. However, technology has a poor track record for 3______social issues without creating unintended harm. What negative effects can we 4______, and how can we refine the objectives of AI researchers to account for such unintended consequences? For decades the holy grail of AI for education has been the creation of an autonomous tutor: an algorithm that can monitor students’ progress, 5______what they know and what motivates them, and provide an optimal, 6______learning experience. With 7______to an autonomous tutor, students can learn from home, anywhere in the world. 8______, autonomous tutors of 2020 look quite different from this ideal. Education with auto-tutors usually 9______students with problems designed to be easy for the algorithm to interpret—as 10______to joyful for the learner. Current algorithms can’t read motivation, and are far from engendering 11______learning gains, instead focusing on engaging students for the short term. The technical challenges are 12______: building the ideal auto-tutor could be as 13______as reaching true general AI. The research community has seen this as a challenge: we simply need to 14______our technical shortcomings to achieve the utopian dream. 15______ is the auto-tutor utopia a dream worth building toward? We offer some dangers that 16______use of artificially intelligent systems such as auto-tutors and call for research into 17______that harness the potential good from application of AI in education, 18______mitigating the risks. We believe our 19______of thoughtfully developed AI systems working in tandem with naturally intelligent humans can 20______a broad community of learners around the world. 第（1）题选______。

Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A 1______in educational content from online courses and the contemporary renaissance in AI seem to provide the conditions 2______to deliver personalized learning at scale. However, technology has a poor track record for 3______social issues without creating unintended harm. What negative effects can we 4______, and how can we refine the objectives of AI researchers to account for such unintended consequences? For decades the holy grail of AI for education has been the creation of an autonomous tutor: an algorithm that can monitor students’ progress, 5______what they know and what motivates them, and provide an optimal, 6______learning experience. With 7______to an autonomous tutor, students can learn from home, anywhere in the world. 8______, autonomous tutors of 2020 look quite different from this ideal. Education with auto-tutors usually 9______students with problems designed to be easy for the algorithm to interpret—as 10______to joyful for the learner. Current algorithms can’t read motivation, and are far from engendering 11______learning gains, instead focusing on engaging students for the short term. The technical challenges are 12______: building the ideal auto-tutor could be as 13______as reaching true general AI. The research community has seen this as a challenge: we simply need to 14______our technical shortcomings to achieve the utopian dream. 15______ is the auto-tutor utopia a dream worth building toward? We offer some dangers that 16______use of artificially intelligent systems such as auto-tutors and call for research into 17______that harness the potential good from application of AI in education, 18______mitigating the risks. We believe our 19______of thoughtfully developed AI systems working in tandem with naturally intelligent humans can 20______a broad community of learners around the world. 第（2）题选______。

Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A 1______in educational content from online courses and the contemporary renaissance in AI seem to provide the conditions 2______to deliver personalized learning at scale. However, technology has a poor track record for 3______social issues without creating unintended harm. What negative effects can we 4______, and how can we refine the objectives of AI researchers to account for such unintended consequences? For decades the holy grail of AI for education has been the creation of an autonomous tutor: an algorithm that can monitor students’ progress, 5______what they know and what motivates them, and provide an optimal, 6______learning experience. With 7______to an autonomous tutor, students can learn from home, anywhere in the world. 8______, autonomous tutors of 2020 look quite different from this ideal. Education with auto-tutors usually 9______students with problems designed to be easy for the algorithm to interpret—as 10______to joyful for the learner. Current algorithms can’t read motivation, and are far from engendering 11______learning gains, instead focusing on engaging students for the short term. The technical challenges are 12______: building the ideal auto-tutor could be as 13______as reaching true general AI. The research community has seen this as a challenge: we simply need to 14______our technical shortcomings to achieve the utopian dream. 15______ is the auto-tutor utopia a dream worth building toward? We offer some dangers that 16______use of artificially intelligent systems such as auto-tutors and call for research into 17______that harness the potential good from application of AI in education, 18______mitigating the risks. We believe our 19______of thoughtfully developed AI systems working in tandem with naturally intelligent humans can 20______a broad community of learners around the world. 第（3）题选______。

Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A 1______in educational content from online courses and the contemporary renaissance in AI seem to provide the conditions 2______to deliver personalized learning at scale. However, technology has a poor track record for 3______social issues without creating unintended harm. What negative effects can we 4______, and how can we refine the objectives of AI researchers to account for such unintended consequences? For decades the holy grail of AI for education has been the creation of an autonomous tutor: an algorithm that can monitor students’ progress, 5______what they know and what motivates them, and provide an optimal, 6______learning experience. With 7______to an autonomous tutor, students can learn from home, anywhere in the world. 8______, autonomous tutors of 2020 look quite different from this ideal. Education with auto-tutors usually 9______students with problems designed to be easy for the algorithm to interpret—as 10______to joyful for the learner. Current algorithms can’t read motivation, and are far from engendering 11______learning gains, instead focusing on engaging students for the short term. The technical challenges are 12______: building the ideal auto-tutor could be as 13______as reaching true general AI. The research community has seen this as a challenge: we simply need to 14______our technical shortcomings to achieve the utopian dream. 15______ is the auto-tutor utopia a dream worth building toward? We offer some dangers that 16______use of artificially intelligent systems such as auto-tutors and call for research into 17______that harness the potential good from application of AI in education, 18______mitigating the risks. We believe our 19______of thoughtfully developed AI systems working in tandem with naturally intelligent humans can 20______a broad community of learners around the world. 第（4）题选______。

Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A 1______in educational content from online courses and the contemporary renaissance in AI seem to provide the conditions 2______to deliver personalized learning at scale. However, technology has a poor track record for 3______social issues without creating unintended harm. What negative effects can we 4______, and how can we refine the objectives of AI researchers to account for such unintended consequences? For decades the holy grail of AI for education has been the creation of an autonomous tutor: an algorithm that can monitor students’ progress, 5______what they know and what motivates them, and provide an optimal, 6______learning experience. With 7______to an autonomous tutor, students can learn from home, anywhere in the world. 8______, autonomous tutors of 2020 look quite different from this ideal. Education with auto-tutors usually 9______students with problems designed to be easy for the algorithm to interpret—as 10______to joyful for the learner. Current algorithms can’t read motivation, and are far from engendering 11______learning gains, instead focusing on engaging students for the short term. The technical challenges are 12______: building the ideal auto-tutor could be as 13______as reaching true general AI. The research community has seen this as a challenge: we simply need to 14______our technical shortcomings to achieve the utopian dream. 15______ is the auto-tutor utopia a dream worth building toward? We offer some dangers that 16______use of artificially intelligent systems such as auto-tutors and call for research into 17______that harness the potential good from application of AI in education, 18______mitigating the risks. We believe our 19______of thoughtfully developed AI systems working in tandem with naturally intelligent humans can 20______a broad community of learners around the world. 第（5）题选______。

Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A 1______in educational content from online courses and the contemporary renaissance in AI seem to provide the conditions 2______to deliver personalized learning at scale. However, technology has a poor track record for 3______social issues without creating unintended harm. What negative effects can we 4______, and how can we refine the objectives of AI researchers to account for such unintended consequences? For decades the holy grail of AI for education has been the creation of an autonomous tutor: an algorithm that can monitor students’ progress, 5______what they know and what motivates them, and provide an optimal, 6______learning experience. With 7______to an autonomous tutor, students can learn from home, anywhere in the world. 8______, autonomous tutors of 2020 look quite different from this ideal. Education with auto-tutors usually 9______students with problems designed to be easy for the algorithm to interpret—as 10______to joyful for the learner. Current algorithms can’t read motivation, and are far from engendering 11______learning gains, instead focusing on engaging students for the short term. The technical challenges are 12______: building the ideal auto-tutor could be as 13______as reaching true general AI. The research community has seen this as a challenge: we simply need to 14______our technical shortcomings to achieve the utopian dream. 15______ is the auto-tutor utopia a dream worth building toward? We offer some dangers that 16______use of artificially intelligent systems such as auto-tutors and call for research into 17______that harness the potential good from application of AI in education, 18______mitigating the risks. We believe our 19______of thoughtfully developed AI systems working in tandem with naturally intelligent humans can 20______a broad community of learners around the world. 第（6）题选______。

Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A 1______in educational content from online courses and the contemporary renaissance in AI seem to provide the conditions 2______to deliver personalized learning at scale. However, technology has a poor track record for 3______social issues without creating unintended harm. What negative effects can we 4______, and how can we refine the objectives of AI researchers to account for such unintended consequences? For decades the holy grail of AI for education has been the creation of an autonomous tutor: an algorithm that can monitor students’ progress, 5______what they know and what motivates them, and provide an optimal, 6______learning experience. With 7______to an autonomous tutor, students can learn from home, anywhere in the world. 8______, autonomous tutors of 2020 look quite different from this ideal. Education with auto-tutors usually 9______students with problems designed to be easy for the algorithm to interpret—as 10______to joyful for the learner. Current algorithms can’t read motivation, and are far from engendering 11______learning gains, instead focusing on engaging students for the short term. The technical challenges are 12______: building the ideal auto-tutor could be as 13______as reaching true general AI. The research community has seen this as a challenge: we simply need to 14______our technical shortcomings to achieve the utopian dream. 15______ is the auto-tutor utopia a dream worth building toward? We offer some dangers that 16______use of artificially intelligent systems such as auto-tutors and call for research into 17______that harness the potential good from application of AI in education, 18______mitigating the risks. We believe our 19______of thoughtfully developed AI systems working in tandem with naturally intelligent humans can 20______a broad community of learners around the world. 第（7）题选______。

Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A 1______in educational content from online courses and the contemporary renaissance in AI seem to provide the conditions 2______to deliver personalized learning at scale. However, technology has a poor track record for 3______social issues without creating unintended harm. What negative effects can we 4______, and how can we refine the objectives of AI researchers to account for such unintended consequences? For decades the holy grail of AI for education has been the creation of an autonomous tutor: an algorithm that can monitor students’ progress, 5______what they know and what motivates them, and provide an optimal, 6______learning experience. With 7______to an autonomous tutor, students can learn from home, anywhere in the world. 8______, autonomous tutors of 2020 look quite different from this ideal. Education with auto-tutors usually 9______students with problems designed to be easy for the algorithm to interpret—as 10______to joyful for the learner. Current algorithms can’t read motivation, and are far from engendering 11______learning gains, instead focusing on engaging students for the short term. The technical challenges are 12______: building the ideal auto-tutor could be as 13______as reaching true general AI. The research community has seen this as a challenge: we simply need to 14______our technical shortcomings to achieve the utopian dream. 15______ is the auto-tutor utopia a dream worth building toward? We offer some dangers that 16______use of artificially intelligent systems such as auto-tutors and call for research into 17______that harness the potential good from application of AI in education, 18______mitigating the risks. We believe our 19______of thoughtfully developed AI systems working in tandem with naturally intelligent humans can 20______a broad community of learners around the world. 第（8）题选______。

Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A 1______in educational content from online courses and the contemporary renaissance in AI seem to provide the conditions 2______to deliver personalized learning at scale. However, technology has a poor track record for 3______social issues without creating unintended harm. What negative effects can we 4______, and how can we refine the objectives of AI researchers to account for such unintended consequences? For decades the holy grail of AI for education has been the creation of an autonomous tutor: an algorithm that can monitor students’ progress, 5______what they know and what motivates them, and provide an optimal, 6______learning experience. With 7______to an autonomous tutor, students can learn from home, anywhere in the world. 8______, autonomous tutors of 2020 look quite different from this ideal. Education with auto-tutors usually 9______students with problems designed to be easy for the algorithm to interpret—as 10______to joyful for the learner. Current algorithms can’t read motivation, and are far from engendering 11______learning gains, instead focusing on engaging students for the short term. The technical challenges are 12______: building the ideal auto-tutor could be as 13______as reaching true general AI. The research community has seen this as a challenge: we simply need to 14______our technical shortcomings to achieve the utopian dream. 15______ is the auto-tutor utopia a dream worth building toward? We offer some dangers that 16______use of artificially intelligent systems such as auto-tutors and call for research into 17______that harness the potential good from application of AI in education, 18______mitigating the risks. We believe our 19______of thoughtfully developed AI systems working in tandem with naturally intelligent humans can 20______a broad community of learners around the world. 第（9）题选______。

Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A 1______in educational content from online courses and the contemporary renaissance in AI seem to provide the conditions 2______to deliver personalized learning at scale. However, technology has a poor track record for 3______social issues without creating unintended harm. What negative effects can we 4______, and how can we refine the objectives of AI researchers to account for such unintended consequences? For decades the holy grail of AI for education has been the creation of an autonomous tutor: an algorithm that can monitor students’ progress, 5______what they know and what motivates them, and provide an optimal, 6______learning experience. With 7______to an autonomous tutor, students can learn from home, anywhere in the world. 8______, autonomous tutors of 2020 look quite different from this ideal. Education with auto-tutors usually 9______students with problems designed to be easy for the algorithm to interpret—as 10______to joyful for the learner. Current algorithms can’t read motivation, and are far from engendering 11______learning gains, instead focusing on engaging students for the short term. The technical challenges are 12______: building the ideal auto-tutor could be as 13______as reaching true general AI. The research community has seen this as a challenge: we simply need to 14______our technical shortcomings to achieve the utopian dream. 15______ is the auto-tutor utopia a dream worth building toward? We offer some dangers that 16______use of artificially intelligent systems such as auto-tutors and call for research into 17______that harness the potential good from application of AI in education, 18______mitigating the risks. We believe our 19______of thoughtfully developed AI systems working in tandem with naturally intelligent humans can 20______a broad community of learners around the world. 第（10）题选______。

Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A 1______in educational content from online courses and the contemporary renaissance in AI seem to provide the conditions 2______to deliver personalized learning at scale. However, technology has a poor track record for 3______social issues without creating unintended harm. What negative effects can we 4______, and how can we refine the objectives of AI researchers to account for such unintended consequences? For decades the holy grail of AI for education has been the creation of an autonomous tutor: an algorithm that can monitor students’ progress, 5______what they know and what motivates them, and provide an optimal, 6______learning experience. With 7______to an autonomous tutor, students can learn from home, anywhere in the world. 8______, autonomous tutors of 2020 look quite different from this ideal. Education with auto-tutors usually 9______students with problems designed to be easy for the algorithm to interpret—as 10______to joyful for the learner. Current algorithms can’t read motivation, and are far from engendering 11______learning gains, instead focusing on engaging students for the short term. The technical challenges are 12______: building the ideal auto-tutor could be as 13______as reaching true general AI. The research community has seen this as a challenge: we simply need to 14______our technical shortcomings to achieve the utopian dream. 15______ is the auto-tutor utopia a dream worth building toward? We offer some dangers that 16______use of artificially intelligent systems such as auto-tutors and call for research into 17______that harness the potential good from application of AI in education, 18______mitigating the risks. We believe our 19______of thoughtfully developed AI systems working in tandem with naturally intelligent humans can 20______a broad community of learners around the world. 第（11）题选______。

Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A 1______in educational content from online courses and the contemporary renaissance in AI seem to provide the conditions 2______to deliver personalized learning at scale. However, technology has a poor track record for 3______social issues without creating unintended harm. What negative effects can we 4______, and how can we refine the objectives of AI researchers to account for such unintended consequences? For decades the holy grail of AI for education has been the creation of an autonomous tutor: an algorithm that can monitor students’ progress, 5______what they know and what motivates them, and provide an optimal, 6______learning experience. With 7______to an autonomous tutor, students can learn from home, anywhere in the world. 8______, autonomous tutors of 2020 look quite different from this ideal. Education with auto-tutors usually 9______students with problems designed to be easy for the algorithm to interpret—as 10______to joyful for the learner. Current algorithms can’t read motivation, and are far from engendering 11______learning gains, instead focusing on engaging students for the short term. The technical challenges are 12______: building the ideal auto-tutor could be as 13______as reaching true general AI. The research community has seen this as a challenge: we simply need to 14______our technical shortcomings to achieve the utopian dream. 15______ is the auto-tutor utopia a dream worth building toward? We offer some dangers that 16______use of artificially intelligent systems such as auto-tutors and call for research into 17______that harness the potential good from application of AI in education, 18______mitigating the risks. We believe our 19______of thoughtfully developed AI systems working in tandem with naturally intelligent humans can 20______a broad community of learners around the world. 第（12）题选______。

Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A 1______in educational content from online courses and the contemporary renaissance in AI seem to provide the conditions 2______to deliver personalized learning at scale. However, technology has a poor track record for 3______social issues without creating unintended harm. What negative effects can we 4______, and how can we refine the objectives of AI researchers to account for such unintended consequences? For decades the holy grail of AI for education has been the creation of an autonomous tutor: an algorithm that can monitor students’ progress, 5______what they know and what motivates them, and provide an optimal, 6______learning experience. With 7______to an autonomous tutor, students can learn from home, anywhere in the world. 8______, autonomous tutors of 2020 look quite different from this ideal. Education with auto-tutors usually 9______students with problems designed to be easy for the algorithm to interpret—as 10______to joyful for the learner. Current algorithms can’t read motivation, and are far from engendering 11______learning gains, instead focusing on engaging students for the short term. The technical challenges are 12______: building the ideal auto-tutor could be as 13______as reaching true general AI. The research community has seen this as a challenge: we simply need to 14______our technical shortcomings to achieve the utopian dream. 15______ is the auto-tutor utopia a dream worth building toward? We offer some dangers that 16______use of artificially intelligent systems such as auto-tutors and call for research into 17______that harness the potential good from application of AI in education, 18______mitigating the risks. We believe our 19______of thoughtfully developed AI systems working in tandem with naturally intelligent humans can 20______a broad community of learners around the world. 第（13）题选______。

Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A 1______in educational content from online courses and the contemporary renaissance in AI seem to provide the conditions 2______to deliver personalized learning at scale. However, technology has a poor track record for 3______social issues without creating unintended harm. What negative effects can we 4______, and how can we refine the objectives of AI researchers to account for such unintended consequences? For decades the holy grail of AI for education has been the creation of an autonomous tutor: an algorithm that can monitor students’ progress, 5______what they know and what motivates them, and provide an optimal, 6______learning experience. With 7______to an autonomous tutor, students can learn from home, anywhere in the world. 8______, autonomous tutors of 2020 look quite different from this ideal. Education with auto-tutors usually 9______students with problems designed to be easy for the algorithm to interpret—as 10______to joyful for the learner. Current algorithms can’t read motivation, and are far from engendering 11______learning gains, instead focusing on engaging students for the short term. The technical challenges are 12______: building the ideal auto-tutor could be as 13______as reaching true general AI. The research community has seen this as a challenge: we simply need to 14______our technical shortcomings to achieve the utopian dream. 15______ is the auto-tutor utopia a dream worth building toward? We offer some dangers that 16______use of artificially intelligent systems such as auto-tutors and call for research into 17______that harness the potential good from application of AI in education, 18______mitigating the risks. We believe our 19______of thoughtfully developed AI systems working in tandem with naturally intelligent humans can 20______a broad community of learners around the world. 第（14）题选______。

Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A 1______in educational content from online courses and the contemporary renaissance in AI seem to provide the conditions 2______to deliver personalized learning at scale. However, technology has a poor track record for 3______social issues without creating unintended harm. What negative effects can we 4______, and how can we refine the objectives of AI researchers to account for such unintended consequences? For decades the holy grail of AI for education has been the creation of an autonomous tutor: an algorithm that can monitor students’ progress, 5______what they know and what motivates them, and provide an optimal, 6______learning experience. With 7______to an autonomous tutor, students can learn from home, anywhere in the world. 8______, autonomous tutors of 2020 look quite different from this ideal. Education with auto-tutors usually 9______students with problems designed to be easy for the algorithm to interpret—as 10______to joyful for the learner. Current algorithms can’t read motivation, and are far from engendering 11______learning gains, instead focusing on engaging students for the short term. The technical challenges are 12______: building the ideal auto-tutor could be as 13______as reaching true general AI. The research community has seen this as a challenge: we simply need to 14______our technical shortcomings to achieve the utopian dream. 15______ is the auto-tutor utopia a dream worth building toward? We offer some dangers that 16______use of artificially intelligent systems such as auto-tutors and call for research into 17______that harness the potential good from application of AI in education, 18______mitigating the risks. We believe our 19______of thoughtfully developed AI systems working in tandem with naturally intelligent humans can 20______a broad community of learners around the world. 第（15）题选______。

Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A 1______in educational content from online courses and the contemporary renaissance in AI seem to provide the conditions 2______to deliver personalized learning at scale. However, technology has a poor track record for 3______social issues without creating unintended harm. What negative effects can we 4______, and how can we refine the objectives of AI researchers to account for such unintended consequences? For decades the holy grail of AI for education has been the creation of an autonomous tutor: an algorithm that can monitor students’ progress, 5______what they know and what motivates them, and provide an optimal, 6______learning experience. With 7______to an autonomous tutor, students can learn from home, anywhere in the world. 8______, autonomous tutors of 2020 look quite different from this ideal. Education with auto-tutors usually 9______students with problems designed to be easy for the algorithm to interpret—as 10______to joyful for the learner. Current algorithms can’t read motivation, and are far from engendering 11______learning gains, instead focusing on engaging students for the short term. The technical challenges are 12______: building the ideal auto-tutor could be as 13______as reaching true general AI. The research community has seen this as a challenge: we simply need to 14______our technical shortcomings to achieve the utopian dream. 15______ is the auto-tutor utopia a dream worth building toward? We offer some dangers that 16______use of artificially intelligent systems such as auto-tutors and call for research into 17______that harness the potential good from application of AI in education, 18______mitigating the risks. We believe our 19______of thoughtfully developed AI systems working in tandem with naturally intelligent humans can 20______a broad community of learners around the world. 第（16）题选______。

Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A 1______in educational content from online courses and the contemporary renaissance in AI seem to provide the conditions 2______to deliver personalized learning at scale. However, technology has a poor track record for 3______social issues without creating unintended harm. What negative effects can we 4______, and how can we refine the objectives of AI researchers to account for such unintended consequences? For decades the holy grail of AI for education has been the creation of an autonomous tutor: an algorithm that can monitor students’ progress, 5______what they know and what motivates them, and provide an optimal, 6______learning experience. With 7______to an autonomous tutor, students can learn from home, anywhere in the world. 8______, autonomous tutors of 2020 look quite different from this ideal. Education with auto-tutors usually 9______students with problems designed to be easy for the algorithm to interpret—as 10______to joyful for the learner. Current algorithms can’t read motivation, and are far from engendering 11______learning gains, instead focusing on engaging students for the short term. The technical challenges are 12______: building the ideal auto-tutor could be as 13______as reaching true general AI. The research community has seen this as a challenge: we simply need to 14______our technical shortcomings to achieve the utopian dream. 15______ is the auto-tutor utopia a dream worth building toward? We offer some dangers that 16______use of artificially intelligent systems such as auto-tutors and call for research into 17______that harness the potential good from application of AI in education, 18______mitigating the risks. We believe our 19______of thoughtfully developed AI systems working in tandem with naturally intelligent humans can 20______a broad community of learners around the world. 第（17）题选______。

Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A 1______in educational content from online courses and the contemporary renaissance in AI seem to provide the conditions 2______to deliver personalized learning at scale. However, technology has a poor track record for 3______social issues without creating unintended harm. What negative effects can we 4______, and how can we refine the objectives of AI researchers to account for such unintended consequences? For decades the holy grail of AI for education has been the creation of an autonomous tutor: an algorithm that can monitor students’ progress, 5______what they know and what motivates them, and provide an optimal, 6______learning experience. With 7______to an autonomous tutor, students can learn from home, anywhere in the world. 8______, autonomous tutors of 2020 look quite different from this ideal. Education with auto-tutors usually 9______students with problems designed to be easy for the algorithm to interpret—as 10______to joyful for the learner. Current algorithms can’t read motivation, and are far from engendering 11______learning gains, instead focusing on engaging students for the short term. The technical challenges are 12______: building the ideal auto-tutor could be as 13______as reaching true general AI. The research community has seen this as a challenge: we simply need to 14______our technical shortcomings to achieve the utopian dream. 15______ is the auto-tutor utopia a dream worth building toward? We offer some dangers that 16______use of artificially intelligent systems such as auto-tutors and call for research into 17______that harness the potential good from application of AI in education, 18______mitigating the risks. We believe our 19______of thoughtfully developed AI systems working in tandem with naturally intelligent humans can 20______a broad community of learners around the world. 第（18）题选______。

Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A 1______in educational content from online courses and the contemporary renaissance in AI seem to provide the conditions 2______to deliver personalized learning at scale. However, technology has a poor track record for 3______social issues without creating unintended harm. What negative effects can we 4______, and how can we refine the objectives of AI researchers to account for such unintended consequences? For decades the holy grail of AI for education has been the creation of an autonomous tutor: an algorithm that can monitor students’ progress, 5______what they know and what motivates them, and provide an optimal, 6______learning experience. With 7______to an autonomous tutor, students can learn from home, anywhere in the world. 8______, autonomous tutors of 2020 look quite different from this ideal. Education with auto-tutors usually 9______students with problems designed to be easy for the algorithm to interpret—as 10______to joyful for the learner. Current algorithms can’t read motivation, and are far from engendering 11______learning gains, instead focusing on engaging students for the short term. The technical challenges are 12______: building the ideal auto-tutor could be as 13______as reaching true general AI. The research community has seen this as a challenge: we simply need to 14______our technical shortcomings to achieve the utopian dream. 15______ is the auto-tutor utopia a dream worth building toward? We offer some dangers that 16______use of artificially intelligent systems such as auto-tutors and call for research into 17______that harness the potential good from application of AI in education, 18______mitigating the risks. We believe our 19______of thoughtfully developed AI systems working in tandem with naturally intelligent humans can 20______a broad community of learners around the world. 第（19）题选______。

Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A 1______in educational content from online courses and the contemporary renaissance in AI seem to provide the conditions 2______to deliver personalized learning at scale. However, technology has a poor track record for 3______social issues without creating unintended harm. What negative effects can we 4______, and how can we refine the objectives of AI researchers to account for such unintended consequences? For decades the holy grail of AI for education has been the creation of an autonomous tutor: an algorithm that can monitor students’ progress, 5______what they know and what motivates them, and provide an optimal, 6______learning experience. With 7______to an autonomous tutor, students can learn from home, anywhere in the world. 8______, autonomous tutors of 2020 look quite different from this ideal. Education with auto-tutors usually 9______students with problems designed to be easy for the algorithm to interpret—as 10______to joyful for the learner. Current algorithms can’t read motivation, and are far from engendering 11______learning gains, instead focusing on engaging students for the short term. The technical challenges are 12______: building the ideal auto-tutor could be as 13______as reaching true general AI. The research community has seen this as a challenge: we simply need to 14______our technical shortcomings to achieve the utopian dream. 15______ is the auto-tutor utopia a dream worth building toward? We offer some dangers that 16______use of artificially intelligent systems such as auto-tutors and call for research into 17______that harness the potential good from application of AI in education, 18______mitigating the risks. We believe our 19______of thoughtfully developed AI systems working in tandem with naturally intelligent humans can 20______a broad community of learners around the world. 第（20）题选______。