Inclusive AI for Healthy Change, Retaining Identity Preservation

研究表明，通过鼓励改变，想象一个人未来的自我可以直接影响到更健康的结果。通过新冠肺炎，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中起到了一定作用。例如，肥胖、少数民族或生活在较贫穷地区会增加住院的几率。英国医学杂志报道，英格兰最贫穷地区的劳动年龄成年人死于新冠肺炎的可能性几乎是最富裕地区的四倍。肥胖可能会导致癌症、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，并有助于教育和升级。例如，鼓励员工在工作场所更健康。CMF是一家B2B2C企业，旨在帮助我们的客户改善他们的健康。这是通过个人在10年或20年后随着生活方式的影响而可视化自己的未来来实现的。重要的是，CMF最近在获得ERDF和UWE S4G资金后转向了SaaS模式，从而产生了一个原型白标生活方式年龄计算器应用程序，已经被世界各地的公司和组织使用。然而，尽管人工智能在健康领域正在开辟新的天地，并拥抱4.0的未来，但美国国家标准与技术研究所(NIST)报告称，来自189个组织的约100名开发人员评估的面部识别算法倾向于白人男性偏见。建议在设计过程中应强调包容性，并考虑到性别、种族、阶级和文化等不同群体。由于成本问题，CMF使用公开可用的图像数据集为年龄模型构建了一款应用程序，这些图像数据倾向于白人名人的脸。包容性创新奖将帮助CMF构建一个更具包容性的图像数据集，以代表我们的多元文化社会。CMF可以开拓商业化的新市场，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。_包容性AI for Healthy Change，Keeping Identity Pervening_项目将从40-50k人脸图像的注释和数据标签开始，以确保针对不同种族、性别和年龄组的无偏见输出。二次注释和标签分类将考虑健康，如体重、皮肤质量、皱纹、太阳黑子和眼袋下。将制定积极年龄结果的基准。

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.