Inclusive AI for Healthy Change, Retaining Identity Preservation

研究表明，想象未来的自己可以鼓励改变，从而对健康产生直接影响。通过COVID-19，我们了解到，生活方式、种族和社会经济因素在人们受到病毒影响的严重程度方面发挥了作用。例如，肥胖、少数民族或居住在较贫困地区增加了住院的机会。《英国医学杂志》（BMJ）报道称，英格兰最贫困地区的工作年龄成年人死于COVID-19的可能性几乎是最富裕地区的四倍。肥胖可能导致癌症、糖尿病和心脏病等可预防的疾病。Change My Face（CMF）软件通过改变行为来解决这些问题，并有助于教育和提高水平。例如，在工作场所鼓励更健康的员工。CMF是一家B2B2C企业，旨在帮助我们的客户改善他们的客户的健康。这是通过个人在10年或20年的时间内可视化他们未来的自我以及生活方式的影响来实现的。重要的是，CMF最近转向SaaS模式，并获得了ERDF & UWE S4 G的资助，从而产生了一个原型白标签生活方式年龄计算器应用程序，该应用程序已被世界各地的公司和组织使用。然而，尽管人工智能正在健康领域开辟新的天地，美国国家标准与技术研究所（NIST）报告称，在拥抱4.0未来的过程中，对来自189家组织（包括东芝、英特尔和微软）的约100名开发人员的面部识别算法进行了评估，结果显示，面部识别算法倾向于白色男性。建议是，在设计过程中应强调包容性，并考虑到不同的群体，如性别，种族，阶级和文化。CMF，由于成本已经建立了一个应用程序的年龄模型使用公开的图像数据集，其中倾向于高加索名人的脸。包容性创新奖将帮助CMF构建一个图像数据集，以更加包容地代表我们的多元文化社会。CMF可以开拓新的商业化市场，包括进入个性化健康（可穿戴设备）和个性化护肤品等新市场的全球机会。Inclusive AI for Healthy Change，Retaining Identity Preservation_项目将开始，对4 - 5万张人脸图像进行注释和数据标签，以确保不同种族、性别和年龄组的无偏见输出。二级注释和标签分类将考虑健康，如体重，皮肤质量，皱纹，太阳黑子和眼袋。将制定积极的年龄成果基准。

Research shows that visualising one's future self has a direct impact on healthier outcomes by encouraging change.With COVID-19 we learnt that lifestyle, ethnicity and socio-economic factors played a part in how badly people were affected by the virus. For example, obesity, ethnic minorities, or living in poorer areas increased the chances of hospitalisation.The BMJ (British Medical Journal) reported that working age adults in England's poorest areas were almost four times more likely to die from COVID-19 than those in the wealthiest areas. Being obese can contribute to preventable diseases such as cancer, diabetes and heart disease.Change My Face (CMF) software addresses these problems by way of behavioural change and helps to educate and level up. For example, encouraging healthier employees in the workplace. CMF is a B2B2C enterprise which aims to help our clients improve their customer's health. This is achieved through individuals visualising their future self in 10 or 20 years' time with the effects of lifestyle.Importantly, CMF recently pivoted to a SaaS model having received ERDF & UWE S4G funding resulting in a prototype whitelabel lifestyle age calculator app which is already in use by companies and organisations around the world.However, although AI is breaking new ground in health, and embracing 4.0 futures, The National Institute of Standards and Technology (NIST) reports that _evaluated facial-recognition algorithms from around 100 developers from 189 organizations, including Toshiba, Intel and Microsoft_ leaned towards a white male bias. Recommendations are that inclusivity should be emphasised in the design process and with consideration for diverse groups such as gender, race, class, and culture.CMF, due to costs have built an app for age models using publicly available image datasets which lean towards caucasian celebrity faces. The Inclusive Innovation Award will help CMF to construct an image dataset to become more inclusive representing our multi-cultural society. CMF can exploit new markets for commercialisation including global opportunities into new markets such as personalised health (wearables) and personalised skincare._Inclusive AI for Healthy Change, Retaining Identity Preservation_ project will begin with the annotation and data labelling of between 40- 50k images of faces to ensure nonbiased outputs for different ethnicities, genders and age groups. Secondary annotation and labelling categorisations will take into consideration health, such as weight, skin quality, wrinkles, sunspots and under eye bags. Benchmark for positive age outcomes will be put into place.