This paper evaluates AI from concrete to Abstract (Queiroz et al. 2021), a recently proposed method that enables awareness among the general public on machine learning. Such is possible due to the use of WiSARD, an easily understandable machine learning mechanism, thus requiring little effort and no technical background from the target users. WiSARD is adherent to digital computing; training consists of writing to RAM-type memories, and classification consists of reading from these memories. The model enables easy visualization and understanding of training and classification tasks' internal realization through ludic activities. Furthermore, the WiSARD model does not require an Internet connection for training and classification, and it can learn from a few or one example. WiSARD can also create "mental images" of what it has learned so far, evidencing key features pertaining to a given class. The AIcon2abs method's effectiveness was assessed through the evaluation of a remote course with a workload of approximately 6 hours. It was completed by thirty-four Brazilian subjects: 5 children between 8 and 11 years old; 5 adolescents between 12 and 17 years old; and 24 adults between 21 and 72 years old. The collected data was analyzed from two perspectives: (i) from the perspective of a pre-experiment (of a mixed methods nature) and (ii) from a phenomenological perspective (of a qualitative nature). AIcon2abs was well-rated by almost 100% of the research subjects, and the data collected revealed quite satisfactory results concerning the intended outcomes. This research has been approved by the CEP/HUCFF/FM/UFRJ Human Research Ethics Committee.

翻译：本文评估了Queiroz等人（2021）近期提出的“从具体到抽象的人工智能”（AIcon2abs）方法，该方法旨在提升公众对机器学习的认知。其可行性源于使用WiSARD这一易于理解的机器学习机制，因此目标用户无需技术背景且投入极少精力即可掌握。WiSARD与数字计算高度契合：训练过程相当于对RAM型存储器进行写入操作，分类过程则相当于从中读取数据。该模型通过寓教于乐的活动，可直观展示训练与分类任务的内部实现过程。此外，WiSARD模型无需网络连接即可完成训练与分类，且能从少量样本甚至单一样本中进行学习。它还能生成所学内容的“心智图像”，突出与特定类别相关的关键特征。研究通过评估一门约6学时的远程课程来检验AIcon2abs方法的有效性。该课程由34名巴西受试者完成：包括5名8至11岁儿童、5名12至17岁青少年以及24名21至72岁成年人。收集的数据从两个视角进行分析：（一）预实验视角（兼具混合方法性质）；（二）现象学视角（具有定性研究性质）。近100%的研究对象对AIcon2abs给予了高度评价，且收集的数据在预期目标上呈现出相当令人满意的结果。本研究已获CEP/HUCFF/FM/UFRJ人类研究伦理委员会批准。